Individual glacier data inspection#
This notebook will walk through steps to read in and organize velocity data and clip it to the extent of a single glacier. The tools we will use include xarray, rioxarray, geopandas, and flox.
To clip its_live data to the extent of a single glacier we will use a vector dataset of glacier outlines, the Randolph Glacier Inventory.
Learning goals:
subset large raster to spatial area of interest
exploring dataset with dask and xarray
dataset inspection using
xarray label and index-based selections
grouped computations and reductions
visualization
First, lets install the python libraries that we’ll need for this notebook:
import geopandas as gpd
import os
import numpy as np
import xarray as xr
import rioxarray as rxr
import matplotlib.pyplot as plt
from shapely.geometry import Polygon
from shapely.geometry import Point
import cartopy
import json
import urllib.request
import pandas as pd
%config InlineBackend.figure_format='retina'
from dask.distributed import Client, LocalCluster
import psutil
import logging
#cluster = LocalCluster(
# n_workers = psutil.cpu_count(logical=True)-1,
# silence_logs = logging.ERROR,
# threads_per_worker=1,
#)
#client = Client(cluster)
#client
Reading in ITS_LIVE data –Initial#
We will use some of the functions we defined in the data access notebook in this notebook and others within this tutorial. They are all stored in the itslivetools.py file. If you cloned this tutorial from its github repository you’ll see that itslivetools.py is in the same directory as our current notebook, so we can import it with the following line:
import itslivetools
First, let’s read in the catalog again:
itslive_catalog = gpd.read_file('https://its-live-data.s3.amazonaws.com/datacubes/catalog_v02.json')
Next, we’ll use the gind_granule_by_point() and read_in_s3() functions to read in the ITS_LIVE zarr datacube as an xarray.Dataset object.
The read_in_s3() function will take a url that points to a zarr data cube stored in an AWS S3 bucket and return an xarray dataset.
I started with chunk_size='auto' which will choose chunk sizes that match the underlying data structure (this is generally ideal). More about choosing good chunk sizes here. If you want to use a different chunk size, specify it when you call the read_in_s3() function.
url = itslivetools.find_granule_by_point([95.180191, 30.645973])
url
'http://its-live-data.s3.amazonaws.com/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.zarr'
dc = itslivetools.read_in_s3(url)
dc
<xarray.Dataset>
Dimensions: (mid_date: 25243, y: 833, x: 833)
Coordinates:
* mid_date (mid_date) datetime64[ns] 2022-06-07T04:21:44...
* x (x) float64 7.001e+05 7.003e+05 ... 8e+05
* y (y) float64 3.4e+06 3.4e+06 ... 3.3e+06 3.3e+06
Data variables: (12/60)
M11 (mid_date, y, x) float32 dask.array<chunksize=(25243, 30, 30), meta=np.ndarray>
M11_dr_to_vr_factor (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
M12 (mid_date, y, x) float32 dask.array<chunksize=(25243, 30, 30), meta=np.ndarray>
M12_dr_to_vr_factor (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
acquisition_date_img1 (mid_date) datetime64[ns] dask.array<chunksize=(25243,), meta=np.ndarray>
acquisition_date_img2 (mid_date) datetime64[ns] dask.array<chunksize=(25243,), meta=np.ndarray>
... ...
vy_error_modeled (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
vy_error_slow (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
vy_error_stationary (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
vy_stable_shift (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
vy_stable_shift_slow (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
vy_stable_shift_stationary (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
Attributes: (12/19)
Conventions: CF-1.8
GDAL_AREA_OR_POINT: Area
author: ITS_LIVE, a NASA MEaSUREs project (its-live.j...
autoRIFT_parameter_file: http://its-live-data.s3.amazonaws.com/autorif...
datacube_software_version: 1.0
date_created: 25-Sep-2023 22:00:23
... ...
s3: s3://its-live-data/datacubes/v2/N30E090/ITS_L...
skipped_granules: s3://its-live-data/datacubes/v2/N30E090/ITS_L...
time_standard_img1: UTC
time_standard_img2: UTC
title: ITS_LIVE datacube of image pair velocities
url: https://its-live-data.s3.amazonaws.com/datacu...- mid_date: 25243
- y: 833
- x: 833
- mid_date(mid_date)datetime64[ns]2022-06-07T04:21:44.211208960 .....
- description :
- midpoint of image 1 and image 2 acquisition date and time with granule's centroid longitude and latitude as microseconds
- standard_name :
- image_pair_center_date_with_time_separation
array(['2022-06-07T04:21:44.211208960', '2018-04-14T04:18:49.171219968', '2017-02-10T16:15:50.660901120', ..., '2013-05-20T04:08:31.155972096', '2015-10-17T04:11:05.527512064', '2015-11-10T04:11:15.457366016'], dtype='datetime64[ns]') - x(x)float647.001e+05 7.003e+05 ... 8e+05
- description :
- x coordinate of projection
- standard_name :
- projection_x_coordinate
array([700132.5, 700252.5, 700372.5, ..., 799732.5, 799852.5, 799972.5])
- y(y)float643.4e+06 3.4e+06 ... 3.3e+06 3.3e+06
- description :
- y coordinate of projection
- standard_name :
- projection_y_coordinate
array([3399907.5, 3399787.5, 3399667.5, ..., 3300307.5, 3300187.5, 3300067.5])
- M11(mid_date, y, x)float32dask.array<chunksize=(25243, 30, 30), meta=np.ndarray>
- description :
- conversion matrix element (1st row, 1st column) that can be multiplied with vx to give range pixel displacement dr (see Eq. A18 in https://www.mdpi.com/2072-4292/13/4/749)
- grid_mapping :
- mapping
- standard_name :
- conversion_matrix_element_11
- units :
- pixel/(meter/year)
Array Chunk Bytes 65.25 GiB 86.66 MiB Shape (25243, 833, 833) (25243, 30, 30) Dask graph 784 chunks in 2 graph layers Data type float32 numpy.ndarray - M11_dr_to_vr_factor(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- multiplicative factor that converts slant range pixel displacement dr to slant range velocity vr
- standard_name :
- M11_dr_to_vr_factor
- units :
- meter/(year*pixel)
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - M12(mid_date, y, x)float32dask.array<chunksize=(25243, 30, 30), meta=np.ndarray>
- description :
- conversion matrix element (1st row, 2nd column) that can be multiplied with vy to give range pixel displacement dr (see Eq. A18 in https://www.mdpi.com/2072-4292/13/4/749)
- grid_mapping :
- mapping
- standard_name :
- conversion_matrix_element_12
- units :
- pixel/(meter/year)
Array Chunk Bytes 65.25 GiB 86.66 MiB Shape (25243, 833, 833) (25243, 30, 30) Dask graph 784 chunks in 2 graph layers Data type float32 numpy.ndarray - M12_dr_to_vr_factor(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- multiplicative factor that converts slant range pixel displacement dr to slant range velocity vr
- standard_name :
- M12_dr_to_vr_factor
- units :
- meter/(year*pixel)
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - acquisition_date_img1(mid_date)datetime64[ns]dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- acquisition date and time of image 1
- standard_name :
- image1_acquition_date
Array Chunk Bytes 197.21 kiB 197.21 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type datetime64[ns] numpy.ndarray - acquisition_date_img2(mid_date)datetime64[ns]dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- acquisition date and time of image 2
- standard_name :
- image2_acquition_date
Array Chunk Bytes 197.21 kiB 197.21 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type datetime64[ns] numpy.ndarray - autoRIFT_software_version(mid_date)<U5dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- version of autoRIFT software
- standard_name :
- autoRIFT_software_version
Array Chunk Bytes 493.03 kiB 493.03 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - chip_size_height(mid_date, y, x)float32dask.array<chunksize=(25243, 30, 30), meta=np.ndarray>
- chip_size_coordinates :
- Optical data: chip_size_coordinates = 'image projection geometry: width = x, height = y'. Radar data: chip_size_coordinates = 'radar geometry: width = range, height = azimuth'
- description :
- height of search template (chip)
- grid_mapping :
- mapping
- standard_name :
- chip_size_height
- units :
- m
- y_pixel_size :
- 10.0
Array Chunk Bytes 65.25 GiB 86.66 MiB Shape (25243, 833, 833) (25243, 30, 30) Dask graph 784 chunks in 2 graph layers Data type float32 numpy.ndarray - chip_size_width(mid_date, y, x)float32dask.array<chunksize=(25243, 30, 30), meta=np.ndarray>
- chip_size_coordinates :
- Optical data: chip_size_coordinates = 'image projection geometry: width = x, height = y'. Radar data: chip_size_coordinates = 'radar geometry: width = range, height = azimuth'
- description :
- width of search template (chip)
- grid_mapping :
- mapping
- standard_name :
- chip_size_width
- units :
- m
- x_pixel_size :
- 10.0
Array Chunk Bytes 65.25 GiB 86.66 MiB Shape (25243, 833, 833) (25243, 30, 30) Dask graph 784 chunks in 2 graph layers Data type float32 numpy.ndarray - date_center(mid_date)datetime64[ns]dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- midpoint of image 1 and image 2 acquisition date
- standard_name :
- image_pair_center_date
Array Chunk Bytes 197.21 kiB 197.21 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type datetime64[ns] numpy.ndarray - date_dt(mid_date)timedelta64[ns]dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- time separation between acquisition of image 1 and image 2
- standard_name :
- image_pair_time_separation
Array Chunk Bytes 197.21 kiB 197.21 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type timedelta64[ns] numpy.ndarray - floatingice(y, x)float32dask.array<chunksize=(833, 833), meta=np.ndarray>
- description :
- floating ice mask, 0 = non-floating-ice, 1 = floating-ice
- flag_meanings :
- non-ice ice
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- floating ice mask
- url :
- https://its-live-data.s3.amazonaws.com/autorift_parameters/v001/N46_0120m_floatingice.tif
Array Chunk Bytes 2.65 MiB 2.65 MiB Shape (833, 833) (833, 833) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - granule_url(mid_date)<U1024dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- original granule URL
- standard_name :
- granule_url
Array Chunk Bytes 98.61 MiB 98.61 MiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - interp_mask(mid_date, y, x)float32dask.array<chunksize=(25243, 30, 30), meta=np.ndarray>
- description :
- light interpolation mask
- flag_meanings :
- measured interpolated
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- interpolated_value_mask
Array Chunk Bytes 65.25 GiB 86.66 MiB Shape (25243, 833, 833) (25243, 30, 30) Dask graph 784 chunks in 2 graph layers Data type float32 numpy.ndarray - landice(y, x)float32dask.array<chunksize=(833, 833), meta=np.ndarray>
- description :
- land ice mask, 0 = non-land-ice, 1 = land-ice
- flag_meanings :
- non-ice ice
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- land ice mask
- url :
- https://its-live-data.s3.amazonaws.com/autorift_parameters/v001/N46_0120m_landice.tif
Array Chunk Bytes 2.65 MiB 2.65 MiB Shape (833, 833) (833, 833) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - mapping()<U1...
- GeoTransform :
- 700072.5 120.0 0 3399967.5 0 -120.0
- crs_wkt :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- false_easting :
- 500000.0
- false_northing :
- 0.0
- grid_mapping_name :
- universal_transverse_mercator
- inverse_flattening :
- 298.257223563
- latitude_of_projection_origin :
- 0.0
- longitude_of_central_meridian :
- 93.0
- proj4text :
- +proj=utm +zone=46 +datum=WGS84 +units=m +no_defs
- scale_factor_at_central_meridian :
- 0.9996
- semi_major_axis :
- 6378137.0
- spatial_epsg :
- 32646
- spatial_ref :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- utm_zone_number :
- 46.0
[1 values with dtype=<U1]
- mission_img1(mid_date)<U1dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- id of the mission that acquired image 1
- standard_name :
- image1_mission
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - mission_img2(mid_date)<U1dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- id of the mission that acquired image 2
- standard_name :
- image2_mission
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - roi_valid_percentage(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- percentage of pixels with a valid velocity estimate determined for the intersection of the full image pair footprint and the region of interest (roi) that defines where autoRIFT tried to estimate a velocity
- standard_name :
- region_of_interest_valid_pixel_percentage
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - satellite_img1(mid_date)<U2dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- id of the satellite that acquired image 1
- standard_name :
- image1_satellite
Array Chunk Bytes 197.21 kiB 197.21 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - satellite_img2(mid_date)<U2dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- id of the satellite that acquired image 2
- standard_name :
- image2_satellite
Array Chunk Bytes 197.21 kiB 197.21 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - sensor_img1(mid_date)<U3dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- id of the sensor that acquired image 1
- standard_name :
- image1_sensor
Array Chunk Bytes 295.82 kiB 295.82 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - sensor_img2(mid_date)<U3dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- id of the sensor that acquired image 2
- standard_name :
- image2_sensor
Array Chunk Bytes 295.82 kiB 295.82 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - stable_count_slow(mid_date)uint16dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- number of valid pixels over slowest 25% of ice
- standard_name :
- stable_count_slow
- units :
- count
Array Chunk Bytes 49.30 kiB 49.30 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type uint16 numpy.ndarray - stable_count_stationary(mid_date)uint16dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- number of valid pixels over stationary or slow-flowing surfaces
- standard_name :
- stable_count_stationary
- units :
- count
Array Chunk Bytes 49.30 kiB 49.30 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type uint16 numpy.ndarray - stable_shift_flag(mid_date)uint8dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- flag for applying velocity bias correction: 0 = no correction; 1 = correction from overlapping stable surface mask (stationary or slow-flowing surfaces with velocity < 15 m/yr)(top priority); 2 = correction from slowest 25% of overlapping velocities (second priority)
- standard_name :
- stable_shift_flag
Array Chunk Bytes 24.65 kiB 24.65 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type uint8 numpy.ndarray - v(mid_date, y, x)float32dask.array<chunksize=(25243, 30, 30), meta=np.ndarray>
- description :
- velocity magnitude
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_velocity
- units :
- meter/year
Array Chunk Bytes 65.25 GiB 86.66 MiB Shape (25243, 833, 833) (25243, 30, 30) Dask graph 784 chunks in 2 graph layers Data type float32 numpy.ndarray - v_error(mid_date, y, x)float32dask.array<chunksize=(25243, 30, 30), meta=np.ndarray>
- description :
- velocity magnitude error
- grid_mapping :
- mapping
- standard_name :
- velocity_error
- units :
- meter/year
Array Chunk Bytes 65.25 GiB 86.66 MiB Shape (25243, 833, 833) (25243, 30, 30) Dask graph 784 chunks in 2 graph layers Data type float32 numpy.ndarray - va(mid_date, y, x)float32dask.array<chunksize=(25243, 30, 30), meta=np.ndarray>
- description :
- velocity in radar azimuth direction
- grid_mapping :
- mapping
Array Chunk Bytes 65.25 GiB 86.66 MiB Shape (25243, 833, 833) (25243, 30, 30) Dask graph 784 chunks in 2 graph layers Data type float32 numpy.ndarray - va_error(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- error for velocity in radar azimuth direction
- standard_name :
- va_error
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - va_error_modeled(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- va_error_modeled
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - va_error_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- va_error_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - va_error_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- va_error_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - va_stable_shift(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- applied va shift calibrated using pixels over stable or slow surfaces
- standard_name :
- va_stable_shift
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - va_stable_shift_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- va shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- va_stable_shift_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - va_stable_shift_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- va shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- va_stable_shift_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vr(mid_date, y, x)float32dask.array<chunksize=(25243, 30, 30), meta=np.ndarray>
- description :
- velocity in radar range direction
- grid_mapping :
- mapping
Array Chunk Bytes 65.25 GiB 86.66 MiB Shape (25243, 833, 833) (25243, 30, 30) Dask graph 784 chunks in 2 graph layers Data type float32 numpy.ndarray - vr_error(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- error for velocity in radar range direction
- standard_name :
- vr_error
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vr_error_modeled(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vr_error_modeled
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vr_error_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vr_error_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vr_error_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vr_error_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vr_stable_shift(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- applied vr shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vr_stable_shift
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vr_stable_shift_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- vr shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vr_stable_shift_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vr_stable_shift_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- vr shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vr_stable_shift_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vx(mid_date, y, x)float32dask.array<chunksize=(25243, 30, 30), meta=np.ndarray>
- description :
- velocity component in x direction
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_x_velocity
- units :
- meter/year
Array Chunk Bytes 65.25 GiB 86.66 MiB Shape (25243, 833, 833) (25243, 30, 30) Dask graph 784 chunks in 2 graph layers Data type float32 numpy.ndarray - vx_error(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- best estimate of x_velocity error: vx_error is populated according to the approach used for the velocity bias correction as indicated in "stable_shift_flag"
- standard_name :
- vx_error
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vx_error_modeled(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vx_error_modeled
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vx_error_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vx_error_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vx_error_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 meter/year identified from an external mask
- standard_name :
- vx_error_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vx_stable_shift(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- applied vx shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vx_stable_shift
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vx_stable_shift_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- vx shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vx_stable_shift_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vx_stable_shift_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- vx shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vx_stable_shift_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vy(mid_date, y, x)float32dask.array<chunksize=(25243, 30, 30), meta=np.ndarray>
- description :
- velocity component in y direction
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_y_velocity
- units :
- meter/year
Array Chunk Bytes 65.25 GiB 86.66 MiB Shape (25243, 833, 833) (25243, 30, 30) Dask graph 784 chunks in 2 graph layers Data type float32 numpy.ndarray - vy_error(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- best estimate of y_velocity error: vy_error is populated according to the approach used for the velocity bias correction as indicated in "stable_shift_flag"
- standard_name :
- vy_error
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vy_error_modeled(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vy_error_modeled
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vy_error_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vy_error_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vy_error_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 meter/year identified from an external mask
- standard_name :
- vy_error_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vy_stable_shift(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- applied vy shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vy_stable_shift
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vy_stable_shift_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- vy shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vy_stable_shift_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vy_stable_shift_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- vy shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vy_stable_shift_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray
- mid_datePandasIndex
PandasIndex(DatetimeIndex(['2022-06-07 04:21:44.211208960', '2018-04-14 04:18:49.171219968', '2017-02-10 16:15:50.660901120', '2022-04-03 04:19:01.211214080', '2021-07-22 04:16:46.210427904', '2019-03-15 04:15:44.180925952', '2002-09-15 03:59:12.379172096', '2002-12-28 03:42:16.181281024', '2021-06-29 16:16:10.210323968', '2022-03-26 16:18:35.211123968', ... '2015-03-15 04:10:27.667560960', '2012-11-25 04:08:32.642952960', '2012-12-27 04:08:58.362065920', '2017-05-27 04:10:08.145324032', '2016-12-06 04:11:32.294059776', '2013-04-18 04:08:52.932247040', '2017-05-07 04:11:30.865388288', '2013-05-20 04:08:31.155972096', '2015-10-17 04:11:05.527512064', '2015-11-10 04:11:15.457366016'], dtype='datetime64[ns]', name='mid_date', length=25243, freq=None)) - xPandasIndex
PandasIndex(Index([700132.5, 700252.5, 700372.5, 700492.5, 700612.5, 700732.5, 700852.5, 700972.5, 701092.5, 701212.5, ... 798892.5, 799012.5, 799132.5, 799252.5, 799372.5, 799492.5, 799612.5, 799732.5, 799852.5, 799972.5], dtype='float64', name='x', length=833)) - yPandasIndex
PandasIndex(Index([3399907.5, 3399787.5, 3399667.5, 3399547.5, 3399427.5, 3399307.5, 3399187.5, 3399067.5, 3398947.5, 3398827.5, ... 3301147.5, 3301027.5, 3300907.5, 3300787.5, 3300667.5, 3300547.5, 3300427.5, 3300307.5, 3300187.5, 3300067.5], dtype='float64', name='y', length=833))
- Conventions :
- CF-1.8
- GDAL_AREA_OR_POINT :
- Area
- author :
- ITS_LIVE, a NASA MEaSUREs project (its-live.jpl.nasa.gov)
- autoRIFT_parameter_file :
- http://its-live-data.s3.amazonaws.com/autorift_parameters/v001/autorift_landice_0120m.shp
- datacube_software_version :
- 1.0
- date_created :
- 25-Sep-2023 22:00:23
- date_updated :
- 25-Sep-2023 22:00:23
- geo_polygon :
- [[95.06959008486952, 29.814255053135895], [95.32812062059084, 29.809951334550703], [95.58659184122865, 29.80514261876954], [95.84499718862224, 29.7998293459177], [96.10333011481168, 29.79401200205343], [96.11032804508507, 30.019297601073085], [96.11740568350054, 30.244573983323825], [96.12456379063154, 30.469841094022847], [96.1318031397002, 30.695098878594504], [95.87110827645229, 30.70112924501256], [95.61033817656023, 30.7066371044805], [95.34949964126946, 30.711621947056347], [95.08859948278467, 30.716083310981194], [95.08376623410525, 30.49063893600811], [95.07898726183609, 30.26518607254204], [95.0742620484426, 30.039724763743482], [95.06959008486952, 29.814255053135895]]
- institution :
- NASA Jet Propulsion Laboratory (JPL), California Institute of Technology
- latitude :
- 30.26
- longitude :
- 95.6
- proj_polygon :
- [[700000, 3300000], [725000.0, 3300000.0], [750000.0, 3300000.0], [775000.0, 3300000.0], [800000, 3300000], [800000.0, 3325000.0], [800000.0, 3350000.0], [800000.0, 3375000.0], [800000, 3400000], [775000.0, 3400000.0], [750000.0, 3400000.0], [725000.0, 3400000.0], [700000, 3400000], [700000.0, 3375000.0], [700000.0, 3350000.0], [700000.0, 3325000.0], [700000, 3300000]]
- projection :
- 32646
- s3 :
- s3://its-live-data/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.zarr
- skipped_granules :
- s3://its-live-data/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.json
- time_standard_img1 :
- UTC
- time_standard_img2 :
- UTC
- title :
- ITS_LIVE datacube of image pair velocities
- url :
- https://its-live-data.s3.amazonaws.com/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.zarr
We are reading this in as a dask array. Let’s take a look at the chunk sizes:
Note
chunksizes shows the largest chunk size. chunks shows the sizes of all chunks along all dims, better if you have irregular chunks
dc.chunksizes
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
Cell In[8], line 1
----> 1 dc.chunksizes
File ~/miniconda3/envs/itslive_tutorial/lib/python3.11/site-packages/xarray/core/dataset.py:2234, in Dataset.chunksizes(self)
2219 @property
2220 def chunksizes(self) -> Mapping[Hashable, tuple[int, ...]]:
2221 """
2222 Mapping from dimension names to block lengths for this dataset's data, or None if
2223 the underlying data is not a dask array.
(...)
2232 xarray.unify_chunks
2233 """
-> 2234 return get_chunksizes(self.variables.values())
File ~/miniconda3/envs/itslive_tutorial/lib/python3.11/site-packages/xarray/core/common.py:1978, in get_chunksizes(variables)
1976 for dim, c in v.chunksizes.items():
1977 if dim in chunks and c != chunks[dim]:
-> 1978 raise ValueError(
1979 f"Object has inconsistent chunks along dimension {dim}. "
1980 "This can be fixed by calling unify_chunks()."
1981 )
1982 chunks[dim] = c
1983 return Frozen(chunks)
ValueError: Object has inconsistent chunks along dimension y. This can be fixed by calling unify_chunks().
Uh-oh, let’s see what’s going on. We called .chunksizes on the xr.Dataset object, so the first thing I’m going to do is select a xr.DataArray within dc and see if the error also arises there.
dc = dc.unify_chunks()
Great, that worked. Now we can see the chunk sizes of the dataset:
dc.chunksizes
Frozen({'mid_date': (25243,), 'y': (30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 23), 'x': (30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 23)})
Note
Setting the dask chunksize to auto at the xr.open_dataset() step will use chunk sizes that most closely resemble the structure of the underlying data. To avoid imposing a chunk size that isn’t a good fit for the data, avoid re-chunking until we have selected a subset of our area of interest from the larger dataset
Check CRS of xr object:
dc.attrs['projection']
'32646'
Let’s take a look at the time dimension (mid_date here). To start with we’ll just print the first 10 values:
for element in range(10):
print(dc.mid_date[element].data)
2022-06-07T04:21:44.211208960
2018-04-14T04:18:49.171219968
2017-02-10T16:15:50.660901120
2022-04-03T04:19:01.211214080
2021-07-22T04:16:46.210427904
2019-03-15T04:15:44.180925952
2002-09-15T03:59:12.379172096
2002-12-28T03:42:16.181281024
2021-06-29T16:16:10.210323968
2022-03-26T16:18:35.211123968
It doesn’t look like the time dimension is in chronological order, let’s fix that:
Note
The following cell is commented out because it produces an error and usually leads to a dead kernel. Let’s try to troubleshoot this below. {add image of error (in screenshots)}
dc_timesorted = dc.sortby(dc['mid_date'])
Note: optional section#
In some test cases, the above cell triggered the following error. While the current version runs fine, I’m including a work around in the following cells in case you encounter this error as well. If you don’t, feel free to skip ahead to the next sub-section heading
Let’s follow some internet advice and try to fix this issue. We will actually start over from the very beginning and read in the dataset using only xarray and not dask.
dc_new = xr.open_dataset(url, engine='zarr')
Now we have an xr.Dataset that is built on numpy arrays rather than dask arrays, which means we can re-index along the time dimension using xarray’s ‘lazy’ functionality:
dc_new_timesorted = dc_new.sortby(dc_new['mid_date'])
for element in range(10):
print(dc_new_timesorted.mid_date[element].data)
1986-09-11T03:31:15.003252992
1986-10-05T03:31:06.144750016
1986-10-21T03:31:34.493249984
1986-11-22T03:29:27.023556992
1986-11-30T03:29:08.710132992
1986-12-08T03:29:55.372057024
1986-12-08T03:33:17.095283968
1986-12-16T03:30:10.645544000
1986-12-24T03:29:52.332120960
1987-01-09T03:30:01.787228992
Great, much easier. Now, we will chunk the dataset.
dc_new_timesorted = dc_new_timesorted.chunk()
dc_new_timesorted.chunks
Frozen({'mid_date': (25243,), 'y': (833,), 'x': (833,)})
dc_new_timesorted
<xarray.Dataset>
Dimensions: (mid_date: 25243, y: 833, x: 833)
Coordinates:
* mid_date (mid_date) datetime64[ns] 1986-09-11T03:31:15...
* x (x) float64 7.001e+05 7.003e+05 ... 8e+05
* y (y) float64 3.4e+06 3.4e+06 ... 3.3e+06 3.3e+06
Data variables: (12/60)
M11 (mid_date, y, x) float32 dask.array<chunksize=(25243, 833, 833), meta=np.ndarray>
M11_dr_to_vr_factor (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
M12 (mid_date, y, x) float32 dask.array<chunksize=(25243, 833, 833), meta=np.ndarray>
M12_dr_to_vr_factor (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
acquisition_date_img1 (mid_date) datetime64[ns] dask.array<chunksize=(25243,), meta=np.ndarray>
acquisition_date_img2 (mid_date) datetime64[ns] dask.array<chunksize=(25243,), meta=np.ndarray>
... ...
vy_error_modeled (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
vy_error_slow (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
vy_error_stationary (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
vy_stable_shift (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
vy_stable_shift_slow (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
vy_stable_shift_stationary (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
Attributes: (12/19)
Conventions: CF-1.8
GDAL_AREA_OR_POINT: Area
author: ITS_LIVE, a NASA MEaSUREs project (its-live.j...
autoRIFT_parameter_file: http://its-live-data.s3.amazonaws.com/autorif...
datacube_software_version: 1.0
date_created: 25-Sep-2023 22:00:23
... ...
s3: s3://its-live-data/datacubes/v2/N30E090/ITS_L...
skipped_granules: s3://its-live-data/datacubes/v2/N30E090/ITS_L...
time_standard_img1: UTC
time_standard_img2: UTC
title: ITS_LIVE datacube of image pair velocities
url: https://its-live-data.s3.amazonaws.com/datacu...- mid_date: 25243
- y: 833
- x: 833
- mid_date(mid_date)datetime64[ns]1986-09-11T03:31:15.003252992 .....
- description :
- midpoint of image 1 and image 2 acquisition date and time with granule's centroid longitude and latitude as microseconds
- standard_name :
- image_pair_center_date_with_time_separation
array(['1986-09-11T03:31:15.003252992', '1986-10-05T03:31:06.144750016', '1986-10-21T03:31:34.493249984', ..., '2023-01-08T04:21:39.230103296', '2023-01-10T16:21:40.230107904', '2023-01-10T16:21:40.230107904'], dtype='datetime64[ns]') - x(x)float647.001e+05 7.003e+05 ... 8e+05
- description :
- x coordinate of projection
- standard_name :
- projection_x_coordinate
array([700132.5, 700252.5, 700372.5, ..., 799732.5, 799852.5, 799972.5])
- y(y)float643.4e+06 3.4e+06 ... 3.3e+06 3.3e+06
- description :
- y coordinate of projection
- standard_name :
- projection_y_coordinate
array([3399907.5, 3399787.5, 3399667.5, ..., 3300307.5, 3300187.5, 3300067.5])
- M11(mid_date, y, x)float32dask.array<chunksize=(25243, 833, 833), meta=np.ndarray>
- description :
- conversion matrix element (1st row, 1st column) that can be multiplied with vx to give range pixel displacement dr (see Eq. A18 in https://www.mdpi.com/2072-4292/13/4/749)
- grid_mapping :
- mapping
- standard_name :
- conversion_matrix_element_11
- units :
- pixel/(meter/year)
Array Chunk Bytes 65.25 GiB 65.25 GiB Shape (25243, 833, 833) (25243, 833, 833) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - M11_dr_to_vr_factor(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- multiplicative factor that converts slant range pixel displacement dr to slant range velocity vr
- standard_name :
- M11_dr_to_vr_factor
- units :
- meter/(year*pixel)
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - M12(mid_date, y, x)float32dask.array<chunksize=(25243, 833, 833), meta=np.ndarray>
- description :
- conversion matrix element (1st row, 2nd column) that can be multiplied with vy to give range pixel displacement dr (see Eq. A18 in https://www.mdpi.com/2072-4292/13/4/749)
- grid_mapping :
- mapping
- standard_name :
- conversion_matrix_element_12
- units :
- pixel/(meter/year)
Array Chunk Bytes 65.25 GiB 65.25 GiB Shape (25243, 833, 833) (25243, 833, 833) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - M12_dr_to_vr_factor(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- multiplicative factor that converts slant range pixel displacement dr to slant range velocity vr
- standard_name :
- M12_dr_to_vr_factor
- units :
- meter/(year*pixel)
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - acquisition_date_img1(mid_date)datetime64[ns]dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- acquisition date and time of image 1
- standard_name :
- image1_acquition_date
Array Chunk Bytes 197.21 kiB 197.21 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type datetime64[ns] numpy.ndarray - acquisition_date_img2(mid_date)datetime64[ns]dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- acquisition date and time of image 2
- standard_name :
- image2_acquition_date
Array Chunk Bytes 197.21 kiB 197.21 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type datetime64[ns] numpy.ndarray - autoRIFT_software_version(mid_date)<U5dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- version of autoRIFT software
- standard_name :
- autoRIFT_software_version
Array Chunk Bytes 493.03 kiB 493.03 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - chip_size_height(mid_date, y, x)float32dask.array<chunksize=(25243, 833, 833), meta=np.ndarray>
- chip_size_coordinates :
- Optical data: chip_size_coordinates = 'image projection geometry: width = x, height = y'. Radar data: chip_size_coordinates = 'radar geometry: width = range, height = azimuth'
- description :
- height of search template (chip)
- grid_mapping :
- mapping
- standard_name :
- chip_size_height
- units :
- m
- y_pixel_size :
- 10.0
Array Chunk Bytes 65.25 GiB 65.25 GiB Shape (25243, 833, 833) (25243, 833, 833) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - chip_size_width(mid_date, y, x)float32dask.array<chunksize=(25243, 833, 833), meta=np.ndarray>
- chip_size_coordinates :
- Optical data: chip_size_coordinates = 'image projection geometry: width = x, height = y'. Radar data: chip_size_coordinates = 'radar geometry: width = range, height = azimuth'
- description :
- width of search template (chip)
- grid_mapping :
- mapping
- standard_name :
- chip_size_width
- units :
- m
- x_pixel_size :
- 10.0
Array Chunk Bytes 65.25 GiB 65.25 GiB Shape (25243, 833, 833) (25243, 833, 833) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - date_center(mid_date)datetime64[ns]dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- midpoint of image 1 and image 2 acquisition date
- standard_name :
- image_pair_center_date
Array Chunk Bytes 197.21 kiB 197.21 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type datetime64[ns] numpy.ndarray - date_dt(mid_date)timedelta64[ns]dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- time separation between acquisition of image 1 and image 2
- standard_name :
- image_pair_time_separation
Array Chunk Bytes 197.21 kiB 197.21 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type timedelta64[ns] numpy.ndarray - floatingice(y, x)float32dask.array<chunksize=(833, 833), meta=np.ndarray>
- description :
- floating ice mask, 0 = non-floating-ice, 1 = floating-ice
- flag_meanings :
- non-ice ice
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- floating ice mask
- url :
- https://its-live-data.s3.amazonaws.com/autorift_parameters/v001/N46_0120m_floatingice.tif
Array Chunk Bytes 2.65 MiB 2.65 MiB Shape (833, 833) (833, 833) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - granule_url(mid_date)<U1024dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- original granule URL
- standard_name :
- granule_url
Array Chunk Bytes 98.61 MiB 98.61 MiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - interp_mask(mid_date, y, x)float32dask.array<chunksize=(25243, 833, 833), meta=np.ndarray>
- description :
- light interpolation mask
- flag_meanings :
- measured interpolated
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- interpolated_value_mask
Array Chunk Bytes 65.25 GiB 65.25 GiB Shape (25243, 833, 833) (25243, 833, 833) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - landice(y, x)float32dask.array<chunksize=(833, 833), meta=np.ndarray>
- description :
- land ice mask, 0 = non-land-ice, 1 = land-ice
- flag_meanings :
- non-ice ice
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- land ice mask
- url :
- https://its-live-data.s3.amazonaws.com/autorift_parameters/v001/N46_0120m_landice.tif
Array Chunk Bytes 2.65 MiB 2.65 MiB Shape (833, 833) (833, 833) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - mapping()<U1...
- GeoTransform :
- 700072.5 120.0 0 3399967.5 0 -120.0
- crs_wkt :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- false_easting :
- 500000.0
- false_northing :
- 0.0
- grid_mapping_name :
- universal_transverse_mercator
- inverse_flattening :
- 298.257223563
- latitude_of_projection_origin :
- 0.0
- longitude_of_central_meridian :
- 93.0
- proj4text :
- +proj=utm +zone=46 +datum=WGS84 +units=m +no_defs
- scale_factor_at_central_meridian :
- 0.9996
- semi_major_axis :
- 6378137.0
- spatial_epsg :
- 32646
- spatial_ref :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- utm_zone_number :
- 46.0
[1 values with dtype=<U1]
- mission_img1(mid_date)<U1dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- id of the mission that acquired image 1
- standard_name :
- image1_mission
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - mission_img2(mid_date)<U1dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- id of the mission that acquired image 2
- standard_name :
- image2_mission
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - roi_valid_percentage(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- percentage of pixels with a valid velocity estimate determined for the intersection of the full image pair footprint and the region of interest (roi) that defines where autoRIFT tried to estimate a velocity
- standard_name :
- region_of_interest_valid_pixel_percentage
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - satellite_img1(mid_date)<U2dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- id of the satellite that acquired image 1
- standard_name :
- image1_satellite
Array Chunk Bytes 197.21 kiB 197.21 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - satellite_img2(mid_date)<U2dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- id of the satellite that acquired image 2
- standard_name :
- image2_satellite
Array Chunk Bytes 197.21 kiB 197.21 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - sensor_img1(mid_date)<U3dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- id of the sensor that acquired image 1
- standard_name :
- image1_sensor
Array Chunk Bytes 295.82 kiB 295.82 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - sensor_img2(mid_date)<U3dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- id of the sensor that acquired image 2
- standard_name :
- image2_sensor
Array Chunk Bytes 295.82 kiB 295.82 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - stable_count_slow(mid_date)uint16dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- number of valid pixels over slowest 25% of ice
- standard_name :
- stable_count_slow
- units :
- count
Array Chunk Bytes 49.30 kiB 49.30 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type uint16 numpy.ndarray - stable_count_stationary(mid_date)uint16dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- number of valid pixels over stationary or slow-flowing surfaces
- standard_name :
- stable_count_stationary
- units :
- count
Array Chunk Bytes 49.30 kiB 49.30 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type uint16 numpy.ndarray - stable_shift_flag(mid_date)uint8dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- flag for applying velocity bias correction: 0 = no correction; 1 = correction from overlapping stable surface mask (stationary or slow-flowing surfaces with velocity < 15 m/yr)(top priority); 2 = correction from slowest 25% of overlapping velocities (second priority)
- standard_name :
- stable_shift_flag
Array Chunk Bytes 24.65 kiB 24.65 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type uint8 numpy.ndarray - v(mid_date, y, x)float32dask.array<chunksize=(25243, 833, 833), meta=np.ndarray>
- description :
- velocity magnitude
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_velocity
- units :
- meter/year
Array Chunk Bytes 65.25 GiB 65.25 GiB Shape (25243, 833, 833) (25243, 833, 833) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - v_error(mid_date, y, x)float32dask.array<chunksize=(25243, 833, 833), meta=np.ndarray>
- description :
- velocity magnitude error
- grid_mapping :
- mapping
- standard_name :
- velocity_error
- units :
- meter/year
Array Chunk Bytes 65.25 GiB 65.25 GiB Shape (25243, 833, 833) (25243, 833, 833) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - va(mid_date, y, x)float32dask.array<chunksize=(25243, 833, 833), meta=np.ndarray>
- description :
- velocity in radar azimuth direction
- grid_mapping :
- mapping
Array Chunk Bytes 65.25 GiB 65.25 GiB Shape (25243, 833, 833) (25243, 833, 833) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - va_error(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- error for velocity in radar azimuth direction
- standard_name :
- va_error
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - va_error_modeled(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- va_error_modeled
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - va_error_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- va_error_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - va_error_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- va_error_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - va_stable_shift(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- applied va shift calibrated using pixels over stable or slow surfaces
- standard_name :
- va_stable_shift
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - va_stable_shift_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- va shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- va_stable_shift_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - va_stable_shift_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- va shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- va_stable_shift_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vr(mid_date, y, x)float32dask.array<chunksize=(25243, 833, 833), meta=np.ndarray>
- description :
- velocity in radar range direction
- grid_mapping :
- mapping
Array Chunk Bytes 65.25 GiB 65.25 GiB Shape (25243, 833, 833) (25243, 833, 833) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vr_error(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- error for velocity in radar range direction
- standard_name :
- vr_error
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vr_error_modeled(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vr_error_modeled
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vr_error_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vr_error_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vr_error_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vr_error_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vr_stable_shift(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- applied vr shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vr_stable_shift
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vr_stable_shift_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- vr shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vr_stable_shift_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vr_stable_shift_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- vr shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vr_stable_shift_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vx(mid_date, y, x)float32dask.array<chunksize=(25243, 833, 833), meta=np.ndarray>
- description :
- velocity component in x direction
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_x_velocity
- units :
- meter/year
Array Chunk Bytes 65.25 GiB 65.25 GiB Shape (25243, 833, 833) (25243, 833, 833) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vx_error(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- best estimate of x_velocity error: vx_error is populated according to the approach used for the velocity bias correction as indicated in "stable_shift_flag"
- standard_name :
- vx_error
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vx_error_modeled(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vx_error_modeled
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vx_error_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vx_error_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vx_error_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 meter/year identified from an external mask
- standard_name :
- vx_error_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vx_stable_shift(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- applied vx shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vx_stable_shift
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vx_stable_shift_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- vx shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vx_stable_shift_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vx_stable_shift_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- vx shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vx_stable_shift_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vy(mid_date, y, x)float32dask.array<chunksize=(25243, 833, 833), meta=np.ndarray>
- description :
- velocity component in y direction
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_y_velocity
- units :
- meter/year
Array Chunk Bytes 65.25 GiB 65.25 GiB Shape (25243, 833, 833) (25243, 833, 833) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vy_error(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- best estimate of y_velocity error: vy_error is populated according to the approach used for the velocity bias correction as indicated in "stable_shift_flag"
- standard_name :
- vy_error
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vy_error_modeled(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vy_error_modeled
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vy_error_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vy_error_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vy_error_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 meter/year identified from an external mask
- standard_name :
- vy_error_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vy_stable_shift(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- applied vy shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vy_stable_shift
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vy_stable_shift_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- vy shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vy_stable_shift_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vy_stable_shift_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- vy shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vy_stable_shift_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray
- mid_datePandasIndex
PandasIndex(DatetimeIndex(['1986-09-11 03:31:15.003252992', '1986-10-05 03:31:06.144750016', '1986-10-21 03:31:34.493249984', '1986-11-22 03:29:27.023556992', '1986-11-30 03:29:08.710132992', '1986-12-08 03:29:55.372057024', '1986-12-08 03:33:17.095283968', '1986-12-16 03:30:10.645544', '1986-12-24 03:29:52.332120960', '1987-01-09 03:30:01.787228992', ... '2023-01-05 16:21:45.221229056', '2023-01-05 16:21:45.221229056', '2023-01-05 16:21:50.230103040', '2023-01-05 16:21:50.230103040', '2023-01-05 16:21:50.230103040', '2023-01-05 16:21:50.230103040', '2023-01-08 04:21:39.230103296', '2023-01-08 04:21:39.230103296', '2023-01-10 16:21:40.230107904', '2023-01-10 16:21:40.230107904'], dtype='datetime64[ns]', name='mid_date', length=25243, freq=None)) - xPandasIndex
PandasIndex(Index([700132.5, 700252.5, 700372.5, 700492.5, 700612.5, 700732.5, 700852.5, 700972.5, 701092.5, 701212.5, ... 798892.5, 799012.5, 799132.5, 799252.5, 799372.5, 799492.5, 799612.5, 799732.5, 799852.5, 799972.5], dtype='float64', name='x', length=833)) - yPandasIndex
PandasIndex(Index([3399907.5, 3399787.5, 3399667.5, 3399547.5, 3399427.5, 3399307.5, 3399187.5, 3399067.5, 3398947.5, 3398827.5, ... 3301147.5, 3301027.5, 3300907.5, 3300787.5, 3300667.5, 3300547.5, 3300427.5, 3300307.5, 3300187.5, 3300067.5], dtype='float64', name='y', length=833))
- Conventions :
- CF-1.8
- GDAL_AREA_OR_POINT :
- Area
- author :
- ITS_LIVE, a NASA MEaSUREs project (its-live.jpl.nasa.gov)
- autoRIFT_parameter_file :
- http://its-live-data.s3.amazonaws.com/autorift_parameters/v001/autorift_landice_0120m.shp
- datacube_software_version :
- 1.0
- date_created :
- 25-Sep-2023 22:00:23
- date_updated :
- 25-Sep-2023 22:00:23
- geo_polygon :
- [[95.06959008486952, 29.814255053135895], [95.32812062059084, 29.809951334550703], [95.58659184122865, 29.80514261876954], [95.84499718862224, 29.7998293459177], [96.10333011481168, 29.79401200205343], [96.11032804508507, 30.019297601073085], [96.11740568350054, 30.244573983323825], [96.12456379063154, 30.469841094022847], [96.1318031397002, 30.695098878594504], [95.87110827645229, 30.70112924501256], [95.61033817656023, 30.7066371044805], [95.34949964126946, 30.711621947056347], [95.08859948278467, 30.716083310981194], [95.08376623410525, 30.49063893600811], [95.07898726183609, 30.26518607254204], [95.0742620484426, 30.039724763743482], [95.06959008486952, 29.814255053135895]]
- institution :
- NASA Jet Propulsion Laboratory (JPL), California Institute of Technology
- latitude :
- 30.26
- longitude :
- 95.6
- proj_polygon :
- [[700000, 3300000], [725000.0, 3300000.0], [750000.0, 3300000.0], [775000.0, 3300000.0], [800000, 3300000], [800000.0, 3325000.0], [800000.0, 3350000.0], [800000.0, 3375000.0], [800000, 3400000], [775000.0, 3400000.0], [750000.0, 3400000.0], [725000.0, 3400000.0], [700000, 3400000], [700000.0, 3375000.0], [700000.0, 3350000.0], [700000.0, 3325000.0], [700000, 3300000]]
- projection :
- 32646
- s3 :
- s3://its-live-data/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.zarr
- skipped_granules :
- s3://its-live-data/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.json
- time_standard_img1 :
- UTC
- time_standard_img2 :
- UTC
- title :
- ITS_LIVE datacube of image pair velocities
- url :
- https://its-live-data.s3.amazonaws.com/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.zarr
You can see in the above object that while we techincally now have a ‘chunked dataset’, the entire object is
chunking_dict = dc.chunksizes
chunking_dict
Frozen({'mid_date': (25243,), 'y': (30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 23), 'x': (30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 23)})
dc_rechunk = dc_new.chunk(chunking_dict)
dc_rechunk.chunks
Frozen({'mid_date': (25243,), 'y': (30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 23), 'x': (30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 23)})
Great, now we have our ITS_LIVE dataset, organized by time and with appropriate chunking. Let’s move on and read in vector data describing some physical features we’d like to examine with the ITS_LIVE dataset.
Read in vector data#
We are going to read in RGI region 15 (SouthAsiaEast). RGI data is downloaded in lat/lon coordinates. We will project it to match the CRS of the ITS_LIVE dataset and then select an individual glacier to begin our analysis.
#se_asia = gpd.read_file('https://github.com/e-marshall/itslive/raw/master/rgi15_southasiaeast.geojson')
se_asia = gpd.read_parquet('rgi7_region15_south_asia_east.parquet')
dc.attrs['projection']
'32646'
#project rgi data to match itslive
#we know the epsg from looking at the 'spatial epsg' attr of the mapping var of the dc object
se_asia_prj = se_asia.to_crs(f'EPSG:{dc.attrs["projection"]}')
se_asia_prj.head(3)
| rgi_id | o1region | o2region | glims_id | anlys_id | subm_id | src_date | cenlon | cenlat | utm_zone | ... | zmin_m | zmax_m | zmed_m | zmean_m | slope_deg | aspect_deg | aspect_sec | dem_source | lmax_m | geometry | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | RGI2000-v7.0-G-15-00001 | 15 | 15-01 | G078088E31398N | 866850 | 752 | 2002-07-10T00:00:00 | 78.087891 | 31.398046 | 44 | ... | 4662.2950 | 4699.2095 | 4669.4720 | 4671.4253 | 13.427070 | 122.267290 | 4 | COPDEM30 | 173 | POLYGON Z ((-924868.476 3571663.111 0.000, -92... |
| 1 | RGI2000-v7.0-G-15-00002 | 15 | 15-01 | G078125E31399N | 867227 | 752 | 2002-07-10T00:00:00 | 78.123699 | 31.397796 | 44 | ... | 4453.3584 | 4705.9920 | 4570.9473 | 4571.2770 | 22.822983 | 269.669144 | 7 | COPDEM30 | 1113 | POLYGON Z ((-921270.161 3571706.471 0.000, -92... |
| 2 | RGI2000-v7.0-G-15-00003 | 15 | 15-01 | G078128E31390N | 867273 | 752 | 2000-08-05T00:00:00 | 78.128510 | 31.390287 | 44 | ... | 4791.7593 | 4858.6807 | 4832.1836 | 4827.6700 | 15.626262 | 212.719681 | 6 | COPDEM30 | 327 | POLYGON Z ((-921061.745 3570342.665 0.000, -92... |
3 rows × 29 columns
Crop RGI to ITS_LIVE extent#
#first, get vector bbox of itslive
bbox_dc = itslivetools.get_bounds_polygon(dc)
bbox_dc['geometry']
0 POLYGON ((700132.500 3300067.500, 799972.500 3...
Name: geometry, dtype: geometry
#project from latlon to local utm
bbox_dc = bbox_dc.to_crs(f'EPSG:{dc.attrs["projection"]}')
bbox_dc
| geometry | |
|---|---|
| 0 | POLYGON ((700132.500 3300067.500, 799972.500 3... |
#plot the outline of the itslive granule and the rgi dataframe together
fig, ax = plt.subplots()
bbox_dc.plot(ax=ax, facecolor='None')
se_asia_prj.plot(ax=ax, facecolor='None')
<Axes: >
#subset rgi to bounds
se_asia_subset = gpd.clip(se_asia_prj, bbox_dc)
se_asia_subset.head()
| rgi_id | o1region | o2region | glims_id | anlys_id | subm_id | src_date | cenlon | cenlat | utm_zone | ... | zmin_m | zmax_m | zmed_m | zmean_m | slope_deg | aspect_deg | aspect_sec | dem_source | lmax_m | geometry | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 16373 | RGI2000-v7.0-G-15-16374 | 15 | 15-03 | G095930E29817N | 930178 | 752 | 2005-09-08T00:00:00 | 95.929916 | 29.817003 | 46 | ... | 4985.7314 | 5274.0435 | 5142.7660 | 5148.8170 | 27.024134 | 139.048110 | 4 | COPDEM30 | 756 | POLYGON Z ((783110.719 3302487.481 0.000, 7831... |
| 16374 | RGI2000-v7.0-G-15-16375 | 15 | 15-03 | G095925E29818N | 930160 | 752 | 2005-09-08T00:00:00 | 95.925181 | 29.818399 | 46 | ... | 4856.2790 | 5054.9253 | 4929.5560 | 4933.6890 | 44.126980 | 211.518448 | 6 | COPDEM30 | 366 | POLYGON Z ((782511.360 3302381.154 0.000, 7825... |
| 16376 | RGI2000-v7.0-G-15-16377 | 15 | 15-03 | G095915E29820N | 930107 | 752 | 2005-09-08T00:00:00 | 95.914583 | 29.819510 | 46 | ... | 5072.8910 | 5150.6196 | 5108.5020 | 5111.7217 | 23.980000 | 219.341537 | 6 | COPDEM30 | 170 | POLYGON Z ((781619.822 3302305.074 0.000, 7816... |
| 16371 | RGI2000-v7.0-G-15-16372 | 15 | 15-03 | G095936E29819N | 930215 | 752 | 2005-09-08T00:00:00 | 95.935554 | 29.819123 | 46 | ... | 4838.7646 | 5194.8840 | 5001.5117 | 4992.3706 | 25.684517 | 128.737870 | 4 | COPDEM30 | 931 | POLYGON Z ((783420.055 3302493.804 0.000, 7834... |
| 15879 | RGI2000-v7.0-G-15-15880 | 15 | 15-03 | G095459E29807N | 928789 | 752 | 1999-07-29T00:00:00 | 95.459374 | 29.807181 | 46 | ... | 3802.1846 | 4155.1255 | 4000.2695 | 4000.4404 | 28.155806 | 116.148640 | 4 | COPDEM30 | 776 | POLYGON Z ((737667.211 3300277.169 0.000, 7377... |
5 rows × 29 columns
We can use the geopandas .explore() method to take a look at the RGI dataset:
se_asia_subset.explore()
/home/emmamarshall/miniconda3/envs/itslive_tutorial/lib/python3.11/site-packages/folium/features.py:1102: UserWarning: GeoJsonTooltip is not configured to render for GeoJson GeometryCollection geometries. Please consider reworking these features: [{'rgi_id': 'RGI2000-v7.0-G-15-16433', 'o1region': '15', 'o2region': '15-03', 'glims_id': 'G095721E29941N', 'anlys_id': 929520, 'subm_id': 752, 'src_date': '2005-09-08T00:00:00', 'cenlon': 95.7211016152286, 'cenlat': 29.940902187781784, 'utm_zone': 46, 'area_km2': 0.340954350813452, 'primeclass': 0, 'conn_lvl': 0, 'surge_type': 0, 'term_type': 9, 'glac_name': None, 'is_rgi6': 0, 'termlon': 95.72222864596793, 'termlat': 29.937137080413784, 'zmin_m': 4657.792, 'zmax_m': 5049.5625, 'zmed_m': 4825.1104, 'zmean_m': 4839.4185, 'slope_deg': 23.704372, 'aspect_deg': 145.20973, 'aspect_sec': 4, 'dem_source': 'COPDEM30', 'lmax_m': 891}, {'rgi_id': 'RGI2000-v7.0-G-15-12194', 'o1region': '15', 'o2region': '15-03', 'glims_id': 'G095869E30315N', 'anlys_id': 929951, 'subm_id': 752, 'src_date': '2005-09-08T00:00:00', 'cenlon': 95.86889789565677, 'cenlat': 30.3147685, 'utm_zone': 46, 'area_km2': 8.797406997273084, 'primeclass': 0, 'conn_lvl': 0, 'surge_type': 0, 'term_type': 9, 'glac_name': None, 'is_rgi6': 0, 'termlon': 95.89518363763428, 'termlat': 30.307036248571297, 'zmin_m': 4642.1445, 'zmax_m': 5278.752, 'zmed_m': 5011.06, 'zmean_m': 4993.9243, 'slope_deg': 12.372513, 'aspect_deg': 81.418945, 'aspect_sec': 3, 'dem_source': 'COPDEM30', 'lmax_m': 4994}, {'rgi_id': 'RGI2000-v7.0-G-15-11941', 'o1region': '15', 'o2region': '15-03', 'glims_id': 'G095301E30377N', 'anlys_id': 928228, 'subm_id': 752, 'src_date': '2007-08-20T00:00:00', 'cenlon': 95.30071978915663, 'cenlat': 30.3770025, 'utm_zone': 46, 'area_km2': 0.267701958906151, 'primeclass': 0, 'conn_lvl': 0, 'surge_type': 0, 'term_type': 9, 'glac_name': None, 'is_rgi6': 0, 'termlon': 95.30345982475616, 'termlat': 30.380097687364806, 'zmin_m': 5475.784, 'zmax_m': 5977.979, 'zmed_m': 5750.727, 'zmean_m': 5759.621, 'slope_deg': 41.069595, 'aspect_deg': 350.3331518173218, 'aspect_sec': 1, 'dem_source': 'COPDEM30', 'lmax_m': 807}] to MultiPolygon for full functionality.
https://tools.ietf.org/html/rfc7946#page-9
warnings.warn(
We’ll choose a single glacier to work with for now:
sample_glacier_vec = se_asia_subset.loc[se_asia_subset['rgi_id'] == 'RGI2000-v7.0-G-15-11754']
sample_glacier_vec
| rgi_id | o1region | o2region | glims_id | anlys_id | subm_id | src_date | cenlon | cenlat | utm_zone | ... | zmin_m | zmax_m | zmed_m | zmean_m | slope_deg | aspect_deg | aspect_sec | dem_source | lmax_m | geometry | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 11753 | RGI2000-v7.0-G-15-11754 | 15 | 15-03 | G095137E30633N | 927615 | 752 | 2002-07-10T00:00:00 | 95.13716 | 30.633165 | 46 | ... | 4275.9062 | 5981.547 | 5257.6377 | 5155.8335 | 16.769985 | 68.71781 | 3 | COPDEM90 | 11563 | POLYGON Z ((700799.699 3387922.813 0.000, 7007... |
1 rows × 29 columns
Clip ITS_LIVE dataset to individual glacier extent#
First, we need to use rio.write_crs() to assign a CRS to the itslive object. If we don’t do that first the rio.clip() command will produce an error
Note: you can only run write_crs() once, because it switches mapping from being a data_var to a coord so if you run it again it will produce a key error looking for a var that doesnt’ exist
dc = dc.rio.write_crs(f"epsg:{dc.attrs['projection']}", inplace=True)
%%time
sample_glacier_raster = dc.rio.clip(sample_glacier_vec.geometry, sample_glacier_vec.crs)
CPU times: user 218 ms, sys: 8.22 ms, total: 226 ms
Wall time: 224 ms
sample_glacier_raster
<xarray.Dataset>
Dimensions: (mid_date: 25243, x: 73, y: 64)
Coordinates:
* mid_date (mid_date) datetime64[ns] 2022-06-07T04:21:44...
* x (x) float64 7.003e+05 7.004e+05 ... 7.089e+05
* y (y) float64 3.395e+06 3.395e+06 ... 3.387e+06
mapping int64 0
Data variables: (12/59)
M11 (mid_date, y, x) float32 dask.array<chunksize=(25243, 16, 29), meta=np.ndarray>
M11_dr_to_vr_factor (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
M12 (mid_date, y, x) float32 dask.array<chunksize=(25243, 16, 29), meta=np.ndarray>
M12_dr_to_vr_factor (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
acquisition_date_img1 (mid_date) datetime64[ns] dask.array<chunksize=(25243,), meta=np.ndarray>
acquisition_date_img2 (mid_date) datetime64[ns] dask.array<chunksize=(25243,), meta=np.ndarray>
... ...
vy_error_modeled (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
vy_error_slow (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
vy_error_stationary (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
vy_stable_shift (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
vy_stable_shift_slow (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
vy_stable_shift_stationary (mid_date) float32 dask.array<chunksize=(25243,), meta=np.ndarray>
Attributes: (12/19)
Conventions: CF-1.8
GDAL_AREA_OR_POINT: Area
author: ITS_LIVE, a NASA MEaSUREs project (its-live.j...
autoRIFT_parameter_file: http://its-live-data.s3.amazonaws.com/autorif...
datacube_software_version: 1.0
date_created: 25-Sep-2023 22:00:23
... ...
s3: s3://its-live-data/datacubes/v2/N30E090/ITS_L...
skipped_granules: s3://its-live-data/datacubes/v2/N30E090/ITS_L...
time_standard_img1: UTC
time_standard_img2: UTC
title: ITS_LIVE datacube of image pair velocities
url: https://its-live-data.s3.amazonaws.com/datacu...- mid_date: 25243
- x: 73
- y: 64
- mid_date(mid_date)datetime64[ns]2022-06-07T04:21:44.211208960 .....
- description :
- midpoint of image 1 and image 2 acquisition date and time with granule's centroid longitude and latitude as microseconds
- standard_name :
- image_pair_center_date_with_time_separation
array(['2022-06-07T04:21:44.211208960', '2018-04-14T04:18:49.171219968', '2017-02-10T16:15:50.660901120', ..., '2013-05-20T04:08:31.155972096', '2015-10-17T04:11:05.527512064', '2015-11-10T04:11:15.457366016'], dtype='datetime64[ns]') - x(x)float647.003e+05 7.004e+05 ... 7.089e+05
- description :
- x coordinate of projection
- standard_name :
- projection_x_coordinate
- axis :
- X
- long_name :
- x coordinate of projection
- units :
- metre
array([700252.5, 700372.5, 700492.5, 700612.5, 700732.5, 700852.5, 700972.5, 701092.5, 701212.5, 701332.5, 701452.5, 701572.5, 701692.5, 701812.5, 701932.5, 702052.5, 702172.5, 702292.5, 702412.5, 702532.5, 702652.5, 702772.5, 702892.5, 703012.5, 703132.5, 703252.5, 703372.5, 703492.5, 703612.5, 703732.5, 703852.5, 703972.5, 704092.5, 704212.5, 704332.5, 704452.5, 704572.5, 704692.5, 704812.5, 704932.5, 705052.5, 705172.5, 705292.5, 705412.5, 705532.5, 705652.5, 705772.5, 705892.5, 706012.5, 706132.5, 706252.5, 706372.5, 706492.5, 706612.5, 706732.5, 706852.5, 706972.5, 707092.5, 707212.5, 707332.5, 707452.5, 707572.5, 707692.5, 707812.5, 707932.5, 708052.5, 708172.5, 708292.5, 708412.5, 708532.5, 708652.5, 708772.5, 708892.5]) - y(y)float643.395e+06 3.395e+06 ... 3.387e+06
- description :
- y coordinate of projection
- standard_name :
- projection_y_coordinate
- axis :
- Y
- long_name :
- y coordinate of projection
- units :
- metre
array([3394627.5, 3394507.5, 3394387.5, 3394267.5, 3394147.5, 3394027.5, 3393907.5, 3393787.5, 3393667.5, 3393547.5, 3393427.5, 3393307.5, 3393187.5, 3393067.5, 3392947.5, 3392827.5, 3392707.5, 3392587.5, 3392467.5, 3392347.5, 3392227.5, 3392107.5, 3391987.5, 3391867.5, 3391747.5, 3391627.5, 3391507.5, 3391387.5, 3391267.5, 3391147.5, 3391027.5, 3390907.5, 3390787.5, 3390667.5, 3390547.5, 3390427.5, 3390307.5, 3390187.5, 3390067.5, 3389947.5, 3389827.5, 3389707.5, 3389587.5, 3389467.5, 3389347.5, 3389227.5, 3389107.5, 3388987.5, 3388867.5, 3388747.5, 3388627.5, 3388507.5, 3388387.5, 3388267.5, 3388147.5, 3388027.5, 3387907.5, 3387787.5, 3387667.5, 3387547.5, 3387427.5, 3387307.5, 3387187.5, 3387067.5]) - mapping()int640
- crs_wkt :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- WGS 84
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- WGS 84 / UTM zone 46N
- grid_mapping_name :
- transverse_mercator
- latitude_of_projection_origin :
- 0.0
- longitude_of_central_meridian :
- 93.0
- false_easting :
- 500000.0
- false_northing :
- 0.0
- scale_factor_at_central_meridian :
- 0.9996
- spatial_ref :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- GeoTransform :
- 700192.5 120.0 0.0 3394687.5 0.0 -120.0
array(0)
- M11(mid_date, y, x)float32dask.array<chunksize=(25243, 16, 29), meta=np.ndarray>
- description :
- conversion matrix element (1st row, 1st column) that can be multiplied with vx to give range pixel displacement dr (see Eq. A18 in https://www.mdpi.com/2072-4292/13/4/749)
- grid_mapping :
- mapping
- standard_name :
- conversion_matrix_element_11
- units :
- pixel/(meter/year)
Array Chunk Bytes 449.89 MiB 86.66 MiB Shape (25243, 64, 73) (25243, 30, 30) Dask graph 9 chunks in 6 graph layers Data type float32 numpy.ndarray - M11_dr_to_vr_factor(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- multiplicative factor that converts slant range pixel displacement dr to slant range velocity vr
- standard_name :
- M11_dr_to_vr_factor
- units :
- meter/(year*pixel)
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - M12(mid_date, y, x)float32dask.array<chunksize=(25243, 16, 29), meta=np.ndarray>
- description :
- conversion matrix element (1st row, 2nd column) that can be multiplied with vy to give range pixel displacement dr (see Eq. A18 in https://www.mdpi.com/2072-4292/13/4/749)
- grid_mapping :
- mapping
- standard_name :
- conversion_matrix_element_12
- units :
- pixel/(meter/year)
Array Chunk Bytes 449.89 MiB 86.66 MiB Shape (25243, 64, 73) (25243, 30, 30) Dask graph 9 chunks in 6 graph layers Data type float32 numpy.ndarray - M12_dr_to_vr_factor(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- multiplicative factor that converts slant range pixel displacement dr to slant range velocity vr
- standard_name :
- M12_dr_to_vr_factor
- units :
- meter/(year*pixel)
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - acquisition_date_img1(mid_date)datetime64[ns]dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- acquisition date and time of image 1
- standard_name :
- image1_acquition_date
Array Chunk Bytes 197.21 kiB 197.21 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type datetime64[ns] numpy.ndarray - acquisition_date_img2(mid_date)datetime64[ns]dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- acquisition date and time of image 2
- standard_name :
- image2_acquition_date
Array Chunk Bytes 197.21 kiB 197.21 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type datetime64[ns] numpy.ndarray - autoRIFT_software_version(mid_date)<U5dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- version of autoRIFT software
- standard_name :
- autoRIFT_software_version
Array Chunk Bytes 493.03 kiB 493.03 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - chip_size_height(mid_date, y, x)float32dask.array<chunksize=(25243, 16, 29), meta=np.ndarray>
- chip_size_coordinates :
- Optical data: chip_size_coordinates = 'image projection geometry: width = x, height = y'. Radar data: chip_size_coordinates = 'radar geometry: width = range, height = azimuth'
- description :
- height of search template (chip)
- grid_mapping :
- mapping
- standard_name :
- chip_size_height
- units :
- m
- y_pixel_size :
- 10.0
Array Chunk Bytes 449.89 MiB 86.66 MiB Shape (25243, 64, 73) (25243, 30, 30) Dask graph 9 chunks in 6 graph layers Data type float32 numpy.ndarray - chip_size_width(mid_date, y, x)float32dask.array<chunksize=(25243, 16, 29), meta=np.ndarray>
- chip_size_coordinates :
- Optical data: chip_size_coordinates = 'image projection geometry: width = x, height = y'. Radar data: chip_size_coordinates = 'radar geometry: width = range, height = azimuth'
- description :
- width of search template (chip)
- grid_mapping :
- mapping
- standard_name :
- chip_size_width
- units :
- m
- x_pixel_size :
- 10.0
Array Chunk Bytes 449.89 MiB 86.66 MiB Shape (25243, 64, 73) (25243, 30, 30) Dask graph 9 chunks in 6 graph layers Data type float32 numpy.ndarray - date_center(mid_date)datetime64[ns]dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- midpoint of image 1 and image 2 acquisition date
- standard_name :
- image_pair_center_date
Array Chunk Bytes 197.21 kiB 197.21 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type datetime64[ns] numpy.ndarray - date_dt(mid_date)timedelta64[ns]dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- time separation between acquisition of image 1 and image 2
- standard_name :
- image_pair_time_separation
Array Chunk Bytes 197.21 kiB 197.21 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type timedelta64[ns] numpy.ndarray - floatingice(y, x)float32dask.array<chunksize=(16, 29), meta=np.ndarray>
- description :
- floating ice mask, 0 = non-floating-ice, 1 = floating-ice
- flag_meanings :
- non-ice ice
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- floating ice mask
- url :
- https://its-live-data.s3.amazonaws.com/autorift_parameters/v001/N46_0120m_floatingice.tif
Array Chunk Bytes 18.25 kiB 3.52 kiB Shape (64, 73) (30, 30) Dask graph 9 chunks in 7 graph layers Data type float32 numpy.ndarray - granule_url(mid_date)<U1024dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- original granule URL
- standard_name :
- granule_url
Array Chunk Bytes 98.61 MiB 98.61 MiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - interp_mask(mid_date, y, x)float32dask.array<chunksize=(25243, 16, 29), meta=np.ndarray>
- description :
- light interpolation mask
- flag_meanings :
- measured interpolated
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- interpolated_value_mask
Array Chunk Bytes 449.89 MiB 86.66 MiB Shape (25243, 64, 73) (25243, 30, 30) Dask graph 9 chunks in 6 graph layers Data type float32 numpy.ndarray - landice(y, x)float32dask.array<chunksize=(16, 29), meta=np.ndarray>
- description :
- land ice mask, 0 = non-land-ice, 1 = land-ice
- flag_meanings :
- non-ice ice
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- land ice mask
- url :
- https://its-live-data.s3.amazonaws.com/autorift_parameters/v001/N46_0120m_landice.tif
Array Chunk Bytes 18.25 kiB 3.52 kiB Shape (64, 73) (30, 30) Dask graph 9 chunks in 7 graph layers Data type float32 numpy.ndarray - mission_img1(mid_date)<U1dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- id of the mission that acquired image 1
- standard_name :
- image1_mission
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - mission_img2(mid_date)<U1dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- id of the mission that acquired image 2
- standard_name :
- image2_mission
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - roi_valid_percentage(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- percentage of pixels with a valid velocity estimate determined for the intersection of the full image pair footprint and the region of interest (roi) that defines where autoRIFT tried to estimate a velocity
- standard_name :
- region_of_interest_valid_pixel_percentage
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - satellite_img1(mid_date)<U2dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- id of the satellite that acquired image 1
- standard_name :
- image1_satellite
Array Chunk Bytes 197.21 kiB 197.21 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - satellite_img2(mid_date)<U2dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- id of the satellite that acquired image 2
- standard_name :
- image2_satellite
Array Chunk Bytes 197.21 kiB 197.21 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - sensor_img1(mid_date)<U3dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- id of the sensor that acquired image 1
- standard_name :
- image1_sensor
Array Chunk Bytes 295.82 kiB 295.82 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - sensor_img2(mid_date)<U3dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- id of the sensor that acquired image 2
- standard_name :
- image2_sensor
Array Chunk Bytes 295.82 kiB 295.82 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type - stable_count_slow(mid_date)uint16dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- number of valid pixels over slowest 25% of ice
- standard_name :
- stable_count_slow
- units :
- count
Array Chunk Bytes 49.30 kiB 49.30 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type uint16 numpy.ndarray - stable_count_stationary(mid_date)uint16dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- number of valid pixels over stationary or slow-flowing surfaces
- standard_name :
- stable_count_stationary
- units :
- count
Array Chunk Bytes 49.30 kiB 49.30 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type uint16 numpy.ndarray - stable_shift_flag(mid_date)uint8dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- flag for applying velocity bias correction: 0 = no correction; 1 = correction from overlapping stable surface mask (stationary or slow-flowing surfaces with velocity < 15 m/yr)(top priority); 2 = correction from slowest 25% of overlapping velocities (second priority)
- standard_name :
- stable_shift_flag
Array Chunk Bytes 24.65 kiB 24.65 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type uint8 numpy.ndarray - v(mid_date, y, x)float32dask.array<chunksize=(25243, 16, 29), meta=np.ndarray>
- description :
- velocity magnitude
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_velocity
- units :
- meter/year
Array Chunk Bytes 449.89 MiB 86.66 MiB Shape (25243, 64, 73) (25243, 30, 30) Dask graph 9 chunks in 6 graph layers Data type float32 numpy.ndarray - v_error(mid_date, y, x)float32dask.array<chunksize=(25243, 16, 29), meta=np.ndarray>
- description :
- velocity magnitude error
- grid_mapping :
- mapping
- standard_name :
- velocity_error
- units :
- meter/year
Array Chunk Bytes 449.89 MiB 86.66 MiB Shape (25243, 64, 73) (25243, 30, 30) Dask graph 9 chunks in 6 graph layers Data type float32 numpy.ndarray - va(mid_date, y, x)float32dask.array<chunksize=(25243, 16, 29), meta=np.ndarray>
- description :
- velocity in radar azimuth direction
- grid_mapping :
- mapping
Array Chunk Bytes 449.89 MiB 86.66 MiB Shape (25243, 64, 73) (25243, 30, 30) Dask graph 9 chunks in 6 graph layers Data type float32 numpy.ndarray - va_error(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- error for velocity in radar azimuth direction
- standard_name :
- va_error
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - va_error_modeled(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- va_error_modeled
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - va_error_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- va_error_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - va_error_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- va_error_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - va_stable_shift(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- applied va shift calibrated using pixels over stable or slow surfaces
- standard_name :
- va_stable_shift
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - va_stable_shift_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- va shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- va_stable_shift_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - va_stable_shift_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- va shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- va_stable_shift_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vr(mid_date, y, x)float32dask.array<chunksize=(25243, 16, 29), meta=np.ndarray>
- description :
- velocity in radar range direction
- grid_mapping :
- mapping
Array Chunk Bytes 449.89 MiB 86.66 MiB Shape (25243, 64, 73) (25243, 30, 30) Dask graph 9 chunks in 6 graph layers Data type float32 numpy.ndarray - vr_error(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- error for velocity in radar range direction
- standard_name :
- vr_error
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vr_error_modeled(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vr_error_modeled
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vr_error_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vr_error_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vr_error_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vr_error_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vr_stable_shift(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- applied vr shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vr_stable_shift
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vr_stable_shift_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- vr shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vr_stable_shift_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vr_stable_shift_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- vr shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vr_stable_shift_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vx(mid_date, y, x)float32dask.array<chunksize=(25243, 16, 29), meta=np.ndarray>
- description :
- velocity component in x direction
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_x_velocity
- units :
- meter/year
Array Chunk Bytes 449.89 MiB 86.66 MiB Shape (25243, 64, 73) (25243, 30, 30) Dask graph 9 chunks in 6 graph layers Data type float32 numpy.ndarray - vx_error(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- best estimate of x_velocity error: vx_error is populated according to the approach used for the velocity bias correction as indicated in "stable_shift_flag"
- standard_name :
- vx_error
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vx_error_modeled(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vx_error_modeled
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vx_error_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vx_error_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vx_error_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 meter/year identified from an external mask
- standard_name :
- vx_error_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vx_stable_shift(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- applied vx shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vx_stable_shift
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vx_stable_shift_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- vx shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vx_stable_shift_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vx_stable_shift_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- vx shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vx_stable_shift_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vy(mid_date, y, x)float32dask.array<chunksize=(25243, 16, 29), meta=np.ndarray>
- description :
- velocity component in y direction
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_y_velocity
- units :
- meter/year
Array Chunk Bytes 449.89 MiB 86.66 MiB Shape (25243, 64, 73) (25243, 30, 30) Dask graph 9 chunks in 6 graph layers Data type float32 numpy.ndarray - vy_error(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- best estimate of y_velocity error: vy_error is populated according to the approach used for the velocity bias correction as indicated in "stable_shift_flag"
- standard_name :
- vy_error
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vy_error_modeled(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vy_error_modeled
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vy_error_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vy_error_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vy_error_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 meter/year identified from an external mask
- standard_name :
- vy_error_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vy_stable_shift(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- applied vy shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vy_stable_shift
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vy_stable_shift_slow(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- vy shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vy_stable_shift_slow
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - vy_stable_shift_stationary(mid_date)float32dask.array<chunksize=(25243,), meta=np.ndarray>
- description :
- vy shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vy_stable_shift_stationary
- units :
- meter/year
Array Chunk Bytes 98.61 kiB 98.61 kiB Shape (25243,) (25243,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray
- mid_datePandasIndex
PandasIndex(DatetimeIndex(['2022-06-07 04:21:44.211208960', '2018-04-14 04:18:49.171219968', '2017-02-10 16:15:50.660901120', '2022-04-03 04:19:01.211214080', '2021-07-22 04:16:46.210427904', '2019-03-15 04:15:44.180925952', '2002-09-15 03:59:12.379172096', '2002-12-28 03:42:16.181281024', '2021-06-29 16:16:10.210323968', '2022-03-26 16:18:35.211123968', ... '2015-03-15 04:10:27.667560960', '2012-11-25 04:08:32.642952960', '2012-12-27 04:08:58.362065920', '2017-05-27 04:10:08.145324032', '2016-12-06 04:11:32.294059776', '2013-04-18 04:08:52.932247040', '2017-05-07 04:11:30.865388288', '2013-05-20 04:08:31.155972096', '2015-10-17 04:11:05.527512064', '2015-11-10 04:11:15.457366016'], dtype='datetime64[ns]', name='mid_date', length=25243, freq=None)) - xPandasIndex
PandasIndex(Index([700252.5, 700372.5, 700492.5, 700612.5, 700732.5, 700852.5, 700972.5, 701092.5, 701212.5, 701332.5, 701452.5, 701572.5, 701692.5, 701812.5, 701932.5, 702052.5, 702172.5, 702292.5, 702412.5, 702532.5, 702652.5, 702772.5, 702892.5, 703012.5, 703132.5, 703252.5, 703372.5, 703492.5, 703612.5, 703732.5, 703852.5, 703972.5, 704092.5, 704212.5, 704332.5, 704452.5, 704572.5, 704692.5, 704812.5, 704932.5, 705052.5, 705172.5, 705292.5, 705412.5, 705532.5, 705652.5, 705772.5, 705892.5, 706012.5, 706132.5, 706252.5, 706372.5, 706492.5, 706612.5, 706732.5, 706852.5, 706972.5, 707092.5, 707212.5, 707332.5, 707452.5, 707572.5, 707692.5, 707812.5, 707932.5, 708052.5, 708172.5, 708292.5, 708412.5, 708532.5, 708652.5, 708772.5, 708892.5], dtype='float64', name='x')) - yPandasIndex
PandasIndex(Index([3394627.5, 3394507.5, 3394387.5, 3394267.5, 3394147.5, 3394027.5, 3393907.5, 3393787.5, 3393667.5, 3393547.5, 3393427.5, 3393307.5, 3393187.5, 3393067.5, 3392947.5, 3392827.5, 3392707.5, 3392587.5, 3392467.5, 3392347.5, 3392227.5, 3392107.5, 3391987.5, 3391867.5, 3391747.5, 3391627.5, 3391507.5, 3391387.5, 3391267.5, 3391147.5, 3391027.5, 3390907.5, 3390787.5, 3390667.5, 3390547.5, 3390427.5, 3390307.5, 3390187.5, 3390067.5, 3389947.5, 3389827.5, 3389707.5, 3389587.5, 3389467.5, 3389347.5, 3389227.5, 3389107.5, 3388987.5, 3388867.5, 3388747.5, 3388627.5, 3388507.5, 3388387.5, 3388267.5, 3388147.5, 3388027.5, 3387907.5, 3387787.5, 3387667.5, 3387547.5, 3387427.5, 3387307.5, 3387187.5, 3387067.5], dtype='float64', name='y'))
- Conventions :
- CF-1.8
- GDAL_AREA_OR_POINT :
- Area
- author :
- ITS_LIVE, a NASA MEaSUREs project (its-live.jpl.nasa.gov)
- autoRIFT_parameter_file :
- http://its-live-data.s3.amazonaws.com/autorift_parameters/v001/autorift_landice_0120m.shp
- datacube_software_version :
- 1.0
- date_created :
- 25-Sep-2023 22:00:23
- date_updated :
- 25-Sep-2023 22:00:23
- geo_polygon :
- [[95.06959008486952, 29.814255053135895], [95.32812062059084, 29.809951334550703], [95.58659184122865, 29.80514261876954], [95.84499718862224, 29.7998293459177], [96.10333011481168, 29.79401200205343], [96.11032804508507, 30.019297601073085], [96.11740568350054, 30.244573983323825], [96.12456379063154, 30.469841094022847], [96.1318031397002, 30.695098878594504], [95.87110827645229, 30.70112924501256], [95.61033817656023, 30.7066371044805], [95.34949964126946, 30.711621947056347], [95.08859948278467, 30.716083310981194], [95.08376623410525, 30.49063893600811], [95.07898726183609, 30.26518607254204], [95.0742620484426, 30.039724763743482], [95.06959008486952, 29.814255053135895]]
- institution :
- NASA Jet Propulsion Laboratory (JPL), California Institute of Technology
- latitude :
- 30.26
- longitude :
- 95.6
- proj_polygon :
- [[700000, 3300000], [725000.0, 3300000.0], [750000.0, 3300000.0], [775000.0, 3300000.0], [800000, 3300000], [800000.0, 3325000.0], [800000.0, 3350000.0], [800000.0, 3375000.0], [800000, 3400000], [775000.0, 3400000.0], [750000.0, 3400000.0], [725000.0, 3400000.0], [700000, 3400000], [700000.0, 3375000.0], [700000.0, 3350000.0], [700000.0, 3325000.0], [700000, 3300000]]
- projection :
- 32646
- s3 :
- s3://its-live-data/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.zarr
- skipped_granules :
- s3://its-live-data/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.json
- time_standard_img1 :
- UTC
- time_standard_img2 :
- UTC
- title :
- ITS_LIVE datacube of image pair velocities
- url :
- https://its-live-data.s3.amazonaws.com/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.zarr
Take a look at the clipped object:
sample_glacier_raster.mid_date
<xarray.DataArray 'mid_date' (mid_date: 25243)>
array(['2022-06-07T04:21:44.211208960', '2018-04-14T04:18:49.171219968',
'2017-02-10T16:15:50.660901120', ..., '2013-05-20T04:08:31.155972096',
'2015-10-17T04:11:05.527512064', '2015-11-10T04:11:15.457366016'],
dtype='datetime64[ns]')
Coordinates:
* mid_date (mid_date) datetime64[ns] 2022-06-07T04:21:44.211208960 ... 201...
mapping int64 0
Attributes:
description: midpoint of image 1 and image 2 acquisition date and time...
standard_name: image_pair_center_date_with_time_separation- mid_date: 25243
- 2022-06-07T04:21:44.211208960 ... 2015-11-10T04:11:15.457366016
array(['2022-06-07T04:21:44.211208960', '2018-04-14T04:18:49.171219968', '2017-02-10T16:15:50.660901120', ..., '2013-05-20T04:08:31.155972096', '2015-10-17T04:11:05.527512064', '2015-11-10T04:11:15.457366016'], dtype='datetime64[ns]') - mid_date(mid_date)datetime64[ns]2022-06-07T04:21:44.211208960 .....
- description :
- midpoint of image 1 and image 2 acquisition date and time with granule's centroid longitude and latitude as microseconds
- standard_name :
- image_pair_center_date_with_time_separation
array(['2022-06-07T04:21:44.211208960', '2018-04-14T04:18:49.171219968', '2017-02-10T16:15:50.660901120', ..., '2013-05-20T04:08:31.155972096', '2015-10-17T04:11:05.527512064', '2015-11-10T04:11:15.457366016'], dtype='datetime64[ns]') - mapping()int640
- crs_wkt :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- WGS 84
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- WGS 84 / UTM zone 46N
- grid_mapping_name :
- transverse_mercator
- latitude_of_projection_origin :
- 0.0
- longitude_of_central_meridian :
- 93.0
- false_easting :
- 500000.0
- false_northing :
- 0.0
- scale_factor_at_central_meridian :
- 0.9996
- spatial_ref :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- GeoTransform :
- 700192.5 120.0 0.0 3394687.5 0.0 -120.0
array(0)
- mid_datePandasIndex
PandasIndex(DatetimeIndex(['2022-06-07 04:21:44.211208960', '2018-04-14 04:18:49.171219968', '2017-02-10 16:15:50.660901120', '2022-04-03 04:19:01.211214080', '2021-07-22 04:16:46.210427904', '2019-03-15 04:15:44.180925952', '2002-09-15 03:59:12.379172096', '2002-12-28 03:42:16.181281024', '2021-06-29 16:16:10.210323968', '2022-03-26 16:18:35.211123968', ... '2015-03-15 04:10:27.667560960', '2012-11-25 04:08:32.642952960', '2012-12-27 04:08:58.362065920', '2017-05-27 04:10:08.145324032', '2016-12-06 04:11:32.294059776', '2013-04-18 04:08:52.932247040', '2017-05-07 04:11:30.865388288', '2013-05-20 04:08:31.155972096', '2015-10-17 04:11:05.527512064', '2015-11-10 04:11:15.457366016'], dtype='datetime64[ns]', name='mid_date', length=25243, freq=None))
- description :
- midpoint of image 1 and image 2 acquisition date and time with granule's centroid longitude and latitude as microseconds
- standard_name :
- image_pair_center_date_with_time_separation
sample_glacier_raster = sample_glacier_raster.where(sample_glacier_raster.mid_date.dt.year > 2016, drop=True)
sample_glacier_raster = sample_glacier_raster.where(sample_glacier_raster.mid_date.dt.year < 2020, drop=True)
What satellite sensors are represented in this time series subset?
set(sample_glacier_raster.satellite_img1.values)
{'1A', '2A', '2B', '7', '8'}
sample_glacier_raster = sample_glacier_raster.compute()
sample_glacier_raster
<xarray.Dataset>
Dimensions: (mid_date: 3974, y: 64, x: 73)
Coordinates:
* mid_date (mid_date) datetime64[ns] 2018-04-14T04:18:49...
* x (x) float64 7.003e+05 7.004e+05 ... 7.089e+05
* y (y) float64 3.395e+06 3.395e+06 ... 3.387e+06
mapping int64 0
Data variables: (12/59)
M11 (mid_date, y, x) float32 nan nan nan ... nan nan
M11_dr_to_vr_factor (mid_date) float32 nan nan nan ... nan nan nan
M12 (mid_date, y, x) float32 nan nan nan ... nan nan
M12_dr_to_vr_factor (mid_date) float32 nan nan nan ... nan nan nan
acquisition_date_img1 (mid_date) datetime64[ns] 2017-12-20T04:21:49...
acquisition_date_img2 (mid_date) datetime64[ns] 2018-08-07T04:15:49...
... ...
vy_error_modeled (mid_date) float32 40.5 28.6 27.4 ... 97.0 166.2
vy_error_slow (mid_date) float32 8.0 1.7 1.2 ... 9.7 11.3 25.4
vy_error_stationary (mid_date) float32 8.0 1.7 1.2 ... 9.7 11.3 25.4
vy_stable_shift (mid_date) float32 8.9 -4.9 -0.7 ... -3.6 -10.8
vy_stable_shift_slow (mid_date) float32 8.9 -4.9 -0.7 ... -3.6 -10.7
vy_stable_shift_stationary (mid_date) float32 8.9 -4.9 -0.7 ... -3.6 -10.8
Attributes: (12/19)
Conventions: CF-1.8
GDAL_AREA_OR_POINT: Area
author: ITS_LIVE, a NASA MEaSUREs project (its-live.j...
autoRIFT_parameter_file: http://its-live-data.s3.amazonaws.com/autorif...
datacube_software_version: 1.0
date_created: 25-Sep-2023 22:00:23
... ...
s3: s3://its-live-data/datacubes/v2/N30E090/ITS_L...
skipped_granules: s3://its-live-data/datacubes/v2/N30E090/ITS_L...
time_standard_img1: UTC
time_standard_img2: UTC
title: ITS_LIVE datacube of image pair velocities
url: https://its-live-data.s3.amazonaws.com/datacu...- mid_date: 3974
- y: 64
- x: 73
- mid_date(mid_date)datetime64[ns]2018-04-14T04:18:49.171219968 .....
- description :
- midpoint of image 1 and image 2 acquisition date and time with granule's centroid longitude and latitude as microseconds
- standard_name :
- image_pair_center_date_with_time_separation
array(['2018-04-14T04:18:49.171219968', '2017-02-10T16:15:50.660901120', '2019-03-15T04:15:44.180925952', ..., '2018-06-11T04:10:57.953189888', '2017-05-27T04:10:08.145324032', '2017-05-07T04:11:30.865388288'], dtype='datetime64[ns]') - x(x)float647.003e+05 7.004e+05 ... 7.089e+05
- description :
- x coordinate of projection
- standard_name :
- projection_x_coordinate
- axis :
- X
- long_name :
- x coordinate of projection
- units :
- metre
array([700252.5, 700372.5, 700492.5, 700612.5, 700732.5, 700852.5, 700972.5, 701092.5, 701212.5, 701332.5, 701452.5, 701572.5, 701692.5, 701812.5, 701932.5, 702052.5, 702172.5, 702292.5, 702412.5, 702532.5, 702652.5, 702772.5, 702892.5, 703012.5, 703132.5, 703252.5, 703372.5, 703492.5, 703612.5, 703732.5, 703852.5, 703972.5, 704092.5, 704212.5, 704332.5, 704452.5, 704572.5, 704692.5, 704812.5, 704932.5, 705052.5, 705172.5, 705292.5, 705412.5, 705532.5, 705652.5, 705772.5, 705892.5, 706012.5, 706132.5, 706252.5, 706372.5, 706492.5, 706612.5, 706732.5, 706852.5, 706972.5, 707092.5, 707212.5, 707332.5, 707452.5, 707572.5, 707692.5, 707812.5, 707932.5, 708052.5, 708172.5, 708292.5, 708412.5, 708532.5, 708652.5, 708772.5, 708892.5]) - y(y)float643.395e+06 3.395e+06 ... 3.387e+06
- description :
- y coordinate of projection
- standard_name :
- projection_y_coordinate
- axis :
- Y
- long_name :
- y coordinate of projection
- units :
- metre
array([3394627.5, 3394507.5, 3394387.5, 3394267.5, 3394147.5, 3394027.5, 3393907.5, 3393787.5, 3393667.5, 3393547.5, 3393427.5, 3393307.5, 3393187.5, 3393067.5, 3392947.5, 3392827.5, 3392707.5, 3392587.5, 3392467.5, 3392347.5, 3392227.5, 3392107.5, 3391987.5, 3391867.5, 3391747.5, 3391627.5, 3391507.5, 3391387.5, 3391267.5, 3391147.5, 3391027.5, 3390907.5, 3390787.5, 3390667.5, 3390547.5, 3390427.5, 3390307.5, 3390187.5, 3390067.5, 3389947.5, 3389827.5, 3389707.5, 3389587.5, 3389467.5, 3389347.5, 3389227.5, 3389107.5, 3388987.5, 3388867.5, 3388747.5, 3388627.5, 3388507.5, 3388387.5, 3388267.5, 3388147.5, 3388027.5, 3387907.5, 3387787.5, 3387667.5, 3387547.5, 3387427.5, 3387307.5, 3387187.5, 3387067.5]) - mapping()int640
- crs_wkt :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- WGS 84
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- WGS 84 / UTM zone 46N
- grid_mapping_name :
- transverse_mercator
- latitude_of_projection_origin :
- 0.0
- longitude_of_central_meridian :
- 93.0
- false_easting :
- 500000.0
- false_northing :
- 0.0
- scale_factor_at_central_meridian :
- 0.9996
- spatial_ref :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- GeoTransform :
- 700192.5 120.0 0.0 3394687.5 0.0 -120.0
array(0)
- M11(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- conversion matrix element (1st row, 1st column) that can be multiplied with vx to give range pixel displacement dr (see Eq. A18 in https://www.mdpi.com/2072-4292/13/4/749)
- grid_mapping :
- mapping
- standard_name :
- conversion_matrix_element_11
- units :
- pixel/(meter/year)
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - M11_dr_to_vr_factor(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- multiplicative factor that converts slant range pixel displacement dr to slant range velocity vr
- standard_name :
- M11_dr_to_vr_factor
- units :
- meter/(year*pixel)
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- M12(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- conversion matrix element (1st row, 2nd column) that can be multiplied with vy to give range pixel displacement dr (see Eq. A18 in https://www.mdpi.com/2072-4292/13/4/749)
- grid_mapping :
- mapping
- standard_name :
- conversion_matrix_element_12
- units :
- pixel/(meter/year)
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - M12_dr_to_vr_factor(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- multiplicative factor that converts slant range pixel displacement dr to slant range velocity vr
- standard_name :
- M12_dr_to_vr_factor
- units :
- meter/(year*pixel)
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- acquisition_date_img1(mid_date)datetime64[ns]2017-12-20T04:21:49 ... 2017-04-...
- description :
- acquisition date and time of image 1
- standard_name :
- image1_acquition_date
array(['2017-12-20T04:21:49.000000000', '2016-09-01T04:15:52.000000000', '2018-09-26T04:15:39.000000000', ..., '2018-03-03T04:11:49.197383936', '2017-04-09T04:09:59.003422976', '2017-04-09T04:09:59.003422976'], dtype='datetime64[ns]') - acquisition_date_img2(mid_date)datetime64[ns]2018-08-07T04:15:49 ... 2017-06-...
- description :
- acquisition date and time of image 2
- standard_name :
- image2_acquition_date
array(['2018-08-07T04:15:49.000000000', '2017-07-23T04:15:49.000000000', '2019-09-01T04:15:49.000000000', ..., '2018-09-19T04:10:06.348390144', '2017-07-14T04:10:16.946407936', '2017-06-04T04:13:02.386535936'], dtype='datetime64[ns]') - autoRIFT_software_version(mid_date)object'1.5.0' '1.5.0' ... '1.5.0' '1.5.0'
- description :
- version of autoRIFT software
- standard_name :
- autoRIFT_software_version
array(['1.5.0', '1.5.0', '1.5.0', ..., '1.5.0', '1.5.0', '1.5.0'], dtype=object) - chip_size_height(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- chip_size_coordinates :
- Optical data: chip_size_coordinates = 'image projection geometry: width = x, height = y'. Radar data: chip_size_coordinates = 'radar geometry: width = range, height = azimuth'
- description :
- height of search template (chip)
- grid_mapping :
- mapping
- standard_name :
- chip_size_height
- units :
- m
- y_pixel_size :
- 10.0
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - chip_size_width(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- chip_size_coordinates :
- Optical data: chip_size_coordinates = 'image projection geometry: width = x, height = y'. Radar data: chip_size_coordinates = 'radar geometry: width = range, height = azimuth'
- description :
- width of search template (chip)
- grid_mapping :
- mapping
- standard_name :
- chip_size_width
- units :
- m
- x_pixel_size :
- 10.0
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - date_center(mid_date)datetime64[ns]2018-04-14T04:18:49 ... 2017-05-...
- description :
- midpoint of image 1 and image 2 acquisition date
- standard_name :
- image_pair_center_date
array(['2018-04-14T04:18:49.000000000', '2017-02-10T16:15:50.500000000', '2019-03-15T04:15:44.000000000', ..., '2018-06-11T04:10:57.772887040', '2017-05-27T04:10:07.974915072', '2017-05-07T04:11:30.694979072'], dtype='datetime64[ns]') - date_dt(mid_date)timedelta64[ns]229 days 23:54:00.087890621 ... ...
- description :
- time separation between acquisition of image 1 and image 2
- standard_name :
- image_pair_time_separation
array([19871640087890621, 28079997363281252, 29376010546875000, ..., 17279897167968747, 8294417797851558, 4838583251953126], dtype='timedelta64[ns]') - floatingice(y, x, mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- floating ice mask, 0 = non-floating-ice, 1 = floating-ice
- flag_meanings :
- non-ice ice
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- floating ice mask
- url :
- https://its-live-data.s3.amazonaws.com/autorift_parameters/v001/N46_0120m_floatingice.tif
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - granule_url(mid_date)object'https://its-live-data.s3.amazon...
- description :
- original granule URL
- standard_name :
- granule_url
array(['https://its-live-data.s3.amazonaws.com/velocity_image_pair/sentinel2/v02/N30E090/S2B_MSIL1C_20171220T042149_N0206_R090_T46RGU_20171220T071238_X_S2B_MSIL1C_20180807T041549_N0206_R090_T46RGU_20180807T080037_G0120V02_P017.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/sentinel2/v02/N30E090/S2A_MSIL1C_20160901T041552_N0204_R090_T46RGV_20160901T042146_X_S2B_MSIL1C_20170723T041549_N0205_R090_T46RGV_20170723T042211_G0120V02_P011.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/sentinel2/v02/N30E090/S2B_MSIL1C_20180926T041539_N0206_R090_T46RFV_20180926T085405_X_S2B_MSIL1C_20190901T041549_N0208_R090_T46RFV_20190901T084626_G0120V02_P051.nc', ..., 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LE07_L1TP_135039_20180303_20200829_02_T1_X_LC08_L1TP_135039_20180919_20200830_02_T1_G0120V02_P004.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170409_20200904_02_T1_X_LC08_L1TP_135039_20170714_20200903_02_T1_G0120V02_P003.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170409_20200904_02_T1_X_LE07_L1TP_135039_20170604_20200831_02_T1_G0120V02_P002.nc'], dtype=object) - interp_mask(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- light interpolation mask
- flag_meanings :
- measured interpolated
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- interpolated_value_mask
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - landice(y, x, mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- land ice mask, 0 = non-land-ice, 1 = land-ice
- flag_meanings :
- non-ice ice
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- land ice mask
- url :
- https://its-live-data.s3.amazonaws.com/autorift_parameters/v001/N46_0120m_landice.tif
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - mission_img1(mid_date)object'S' 'S' 'S' 'S' ... 'L' 'L' 'L' 'L'
- description :
- id of the mission that acquired image 1
- standard_name :
- image1_mission
array(['S', 'S', 'S', ..., 'L', 'L', 'L'], dtype=object)
- mission_img2(mid_date)object'S' 'S' 'S' 'S' ... 'L' 'L' 'L' 'L'
- description :
- id of the mission that acquired image 2
- standard_name :
- image2_mission
array(['S', 'S', 'S', ..., 'L', 'L', 'L'], dtype=object)
- roi_valid_percentage(mid_date)float3217.8 11.1 51.2 27.2 ... 4.0 3.2 2.0
- description :
- percentage of pixels with a valid velocity estimate determined for the intersection of the full image pair footprint and the region of interest (roi) that defines where autoRIFT tried to estimate a velocity
- standard_name :
- region_of_interest_valid_pixel_percentage
array([17.8, 11.1, 51.2, ..., 4. , 3.2, 2. ], dtype=float32)
- satellite_img1(mid_date)object'2B' '2A' '2B' '2B' ... '7' '8' '8'
- description :
- id of the satellite that acquired image 1
- standard_name :
- image1_satellite
array(['2B', '2A', '2B', ..., '7', '8', '8'], dtype=object)
- satellite_img2(mid_date)object'2B' '2B' '2B' '2A' ... '8' '8' '7'
- description :
- id of the satellite that acquired image 2
- standard_name :
- image2_satellite
array(['2B', '2B', '2B', ..., '8', '8', '7'], dtype=object)
- sensor_img1(mid_date)object'MSI' 'MSI' 'MSI' ... 'E' 'C' 'C'
- description :
- id of the sensor that acquired image 1
- standard_name :
- image1_sensor
array(['MSI', 'MSI', 'MSI', ..., 'E', 'C', 'C'], dtype=object)
- sensor_img2(mid_date)object'MSI' 'MSI' 'MSI' ... 'C' 'C' 'E'
- description :
- id of the sensor that acquired image 2
- standard_name :
- image2_sensor
array(['MSI', 'MSI', 'MSI', ..., 'C', 'C', 'E'], dtype=object)
- stable_count_slow(mid_date)float648.941e+03 3.531e+04 ... 3.688e+04
- description :
- number of valid pixels over slowest 25% of ice
- standard_name :
- stable_count_slow
- units :
- count
array([ 8941., 35311., 35175., ..., 6346., 741., 36880.])
- stable_count_stationary(mid_date)float648.446e+03 3.529e+04 ... 3.666e+04
- description :
- number of valid pixels over stationary or slow-flowing surfaces
- standard_name :
- stable_count_stationary
- units :
- count
array([ 8446., 35290., 34638., ..., 6286., 64491., 36655.])
- stable_shift_flag(mid_date)float641.0 1.0 1.0 1.0 ... 1.0 1.0 1.0 1.0
- description :
- flag for applying velocity bias correction: 0 = no correction; 1 = correction from overlapping stable surface mask (stationary or slow-flowing surfaces with velocity < 15 m/yr)(top priority); 2 = correction from slowest 25% of overlapping velocities (second priority)
- standard_name :
- stable_shift_flag
array([1., 1., 1., ..., 1., 1., 1.])
- v(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity magnitude
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_velocity
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - v_error(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity magnitude error
- grid_mapping :
- mapping
- standard_name :
- velocity_error
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - va(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity in radar azimuth direction
- grid_mapping :
- mapping
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - va_error(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- error for velocity in radar azimuth direction
- standard_name :
- va_error
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- va_error_modeled(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- va_error_modeled
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- va_error_slow(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- va_error_slow
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- va_error_stationary(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- va_error_stationary
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- va_stable_shift(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- applied va shift calibrated using pixels over stable or slow surfaces
- standard_name :
- va_stable_shift
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- va_stable_shift_slow(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- va shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- va_stable_shift_slow
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- va_stable_shift_stationary(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- va shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- va_stable_shift_stationary
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- vr(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity in radar range direction
- grid_mapping :
- mapping
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - vr_error(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- error for velocity in radar range direction
- standard_name :
- vr_error
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- vr_error_modeled(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vr_error_modeled
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- vr_error_slow(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vr_error_slow
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- vr_error_stationary(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vr_error_stationary
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- vr_stable_shift(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- applied vr shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vr_stable_shift
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- vr_stable_shift_slow(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- vr shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vr_stable_shift_slow
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- vr_stable_shift_stationary(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- vr shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vr_stable_shift_stationary
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- vx(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity component in x direction
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_x_velocity
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - vx_error(mid_date)float323.3 1.3 1.2 4.9 ... 11.7 11.3 51.0
- description :
- best estimate of x_velocity error: vx_error is populated according to the approach used for the velocity bias correction as indicated in "stable_shift_flag"
- standard_name :
- vx_error
- units :
- meter/year
array([ 3.3, 1.3, 1.2, ..., 11.7, 11.3, 51. ], dtype=float32)
- vx_error_modeled(mid_date)float3240.5 28.6 27.4 ... 46.5 97.0 166.2
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vx_error_modeled
- units :
- meter/year
array([ 40.5, 28.6, 27.4, ..., 46.5, 97. , 166.2], dtype=float32)
- vx_error_slow(mid_date)float323.3 1.3 1.2 4.9 ... 11.6 11.2 50.9
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vx_error_slow
- units :
- meter/year
array([ 3.3, 1.3, 1.2, ..., 11.6, 11.2, 50.9], dtype=float32)
- vx_error_stationary(mid_date)float323.3 1.3 1.2 4.9 ... 11.7 11.3 51.0
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 meter/year identified from an external mask
- standard_name :
- vx_error_stationary
- units :
- meter/year
array([ 3.3, 1.3, 1.2, ..., 11.7, 11.3, 51. ], dtype=float32)
- vx_stable_shift(mid_date)float32-1.0 -2.1 5.9 4.8 ... -0.3 3.6 30.8
- description :
- applied vx shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vx_stable_shift
- units :
- meter/year
array([-1. , -2.1, 5.9, ..., -0.3, 3.6, 30.8], dtype=float32)
- vx_stable_shift_slow(mid_date)float32-1.0 -2.1 5.9 4.8 ... -0.2 3.6 30.5
- description :
- vx shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vx_stable_shift_slow
- units :
- meter/year
array([-1. , -2.1, 5.9, ..., -0.2, 3.6, 30.5], dtype=float32)
- vx_stable_shift_stationary(mid_date)float32-1.0 -2.1 5.9 4.8 ... -0.3 3.6 30.8
- description :
- vx shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vx_stable_shift_stationary
- units :
- meter/year
array([-1. , -2.1, 5.9, ..., -0.3, 3.6, 30.8], dtype=float32)
- vy(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity component in y direction
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_y_velocity
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - vy_error(mid_date)float328.0 1.7 1.2 7.4 ... 9.7 11.3 25.4
- description :
- best estimate of y_velocity error: vy_error is populated according to the approach used for the velocity bias correction as indicated in "stable_shift_flag"
- standard_name :
- vy_error
- units :
- meter/year
array([ 8. , 1.7, 1.2, ..., 9.7, 11.3, 25.4], dtype=float32)
- vy_error_modeled(mid_date)float3240.5 28.6 27.4 ... 46.5 97.0 166.2
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vy_error_modeled
- units :
- meter/year
array([ 40.5, 28.6, 27.4, ..., 46.5, 97. , 166.2], dtype=float32)
- vy_error_slow(mid_date)float328.0 1.7 1.2 7.4 ... 9.7 11.3 25.4
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vy_error_slow
- units :
- meter/year
array([ 8. , 1.7, 1.2, ..., 9.7, 11.3, 25.4], dtype=float32)
- vy_error_stationary(mid_date)float328.0 1.7 1.2 7.4 ... 9.7 11.3 25.4
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 meter/year identified from an external mask
- standard_name :
- vy_error_stationary
- units :
- meter/year
array([ 8. , 1.7, 1.2, ..., 9.7, 11.3, 25.4], dtype=float32)
- vy_stable_shift(mid_date)float328.9 -4.9 -0.7 ... 3.4 -3.6 -10.8
- description :
- applied vy shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vy_stable_shift
- units :
- meter/year
array([ 8.9, -4.9, -0.7, ..., 3.4, -3.6, -10.8], dtype=float32)
- vy_stable_shift_slow(mid_date)float328.9 -4.9 -0.7 ... 3.4 -3.6 -10.7
- description :
- vy shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vy_stable_shift_slow
- units :
- meter/year
array([ 8.9, -4.9, -0.7, ..., 3.4, -3.6, -10.7], dtype=float32)
- vy_stable_shift_stationary(mid_date)float328.9 -4.9 -0.7 ... 3.4 -3.6 -10.8
- description :
- vy shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vy_stable_shift_stationary
- units :
- meter/year
array([ 8.9, -4.9, -0.7, ..., 3.4, -3.6, -10.8], dtype=float32)
- mid_datePandasIndex
PandasIndex(DatetimeIndex(['2018-04-14 04:18:49.171219968', '2017-02-10 16:15:50.660901120', '2019-03-15 04:15:44.180925952', '2019-07-20 16:15:55.190603008', '2018-01-31 16:15:50.170811904', '2017-12-17 16:15:50.170508800', '2017-10-16 04:18:49.170811904', '2017-11-27 16:20:45.171105024', '2017-10-08 16:17:55.170906112', '2019-10-23 16:18:15.191001088', ... '2017-10-06 04:11:40.987761920', '2018-03-31 04:10:01.464065024', '2018-06-11 04:09:32.921265664', '2017-07-26 04:11:49.029760256', '2017-04-21 04:11:32.560144896', '2017-09-12 04:11:46.053865984', '2017-06-24 04:11:18.708142080', '2018-06-11 04:10:57.953189888', '2017-05-27 04:10:08.145324032', '2017-05-07 04:11:30.865388288'], dtype='datetime64[ns]', name='mid_date', length=3974, freq=None)) - xPandasIndex
PandasIndex(Index([700252.5, 700372.5, 700492.5, 700612.5, 700732.5, 700852.5, 700972.5, 701092.5, 701212.5, 701332.5, 701452.5, 701572.5, 701692.5, 701812.5, 701932.5, 702052.5, 702172.5, 702292.5, 702412.5, 702532.5, 702652.5, 702772.5, 702892.5, 703012.5, 703132.5, 703252.5, 703372.5, 703492.5, 703612.5, 703732.5, 703852.5, 703972.5, 704092.5, 704212.5, 704332.5, 704452.5, 704572.5, 704692.5, 704812.5, 704932.5, 705052.5, 705172.5, 705292.5, 705412.5, 705532.5, 705652.5, 705772.5, 705892.5, 706012.5, 706132.5, 706252.5, 706372.5, 706492.5, 706612.5, 706732.5, 706852.5, 706972.5, 707092.5, 707212.5, 707332.5, 707452.5, 707572.5, 707692.5, 707812.5, 707932.5, 708052.5, 708172.5, 708292.5, 708412.5, 708532.5, 708652.5, 708772.5, 708892.5], dtype='float64', name='x')) - yPandasIndex
PandasIndex(Index([3394627.5, 3394507.5, 3394387.5, 3394267.5, 3394147.5, 3394027.5, 3393907.5, 3393787.5, 3393667.5, 3393547.5, 3393427.5, 3393307.5, 3393187.5, 3393067.5, 3392947.5, 3392827.5, 3392707.5, 3392587.5, 3392467.5, 3392347.5, 3392227.5, 3392107.5, 3391987.5, 3391867.5, 3391747.5, 3391627.5, 3391507.5, 3391387.5, 3391267.5, 3391147.5, 3391027.5, 3390907.5, 3390787.5, 3390667.5, 3390547.5, 3390427.5, 3390307.5, 3390187.5, 3390067.5, 3389947.5, 3389827.5, 3389707.5, 3389587.5, 3389467.5, 3389347.5, 3389227.5, 3389107.5, 3388987.5, 3388867.5, 3388747.5, 3388627.5, 3388507.5, 3388387.5, 3388267.5, 3388147.5, 3388027.5, 3387907.5, 3387787.5, 3387667.5, 3387547.5, 3387427.5, 3387307.5, 3387187.5, 3387067.5], dtype='float64', name='y'))
- Conventions :
- CF-1.8
- GDAL_AREA_OR_POINT :
- Area
- author :
- ITS_LIVE, a NASA MEaSUREs project (its-live.jpl.nasa.gov)
- autoRIFT_parameter_file :
- http://its-live-data.s3.amazonaws.com/autorift_parameters/v001/autorift_landice_0120m.shp
- datacube_software_version :
- 1.0
- date_created :
- 25-Sep-2023 22:00:23
- date_updated :
- 25-Sep-2023 22:00:23
- geo_polygon :
- [[95.06959008486952, 29.814255053135895], [95.32812062059084, 29.809951334550703], [95.58659184122865, 29.80514261876954], [95.84499718862224, 29.7998293459177], [96.10333011481168, 29.79401200205343], [96.11032804508507, 30.019297601073085], [96.11740568350054, 30.244573983323825], [96.12456379063154, 30.469841094022847], [96.1318031397002, 30.695098878594504], [95.87110827645229, 30.70112924501256], [95.61033817656023, 30.7066371044805], [95.34949964126946, 30.711621947056347], [95.08859948278467, 30.716083310981194], [95.08376623410525, 30.49063893600811], [95.07898726183609, 30.26518607254204], [95.0742620484426, 30.039724763743482], [95.06959008486952, 29.814255053135895]]
- institution :
- NASA Jet Propulsion Laboratory (JPL), California Institute of Technology
- latitude :
- 30.26
- longitude :
- 95.6
- proj_polygon :
- [[700000, 3300000], [725000.0, 3300000.0], [750000.0, 3300000.0], [775000.0, 3300000.0], [800000, 3300000], [800000.0, 3325000.0], [800000.0, 3350000.0], [800000.0, 3375000.0], [800000, 3400000], [775000.0, 3400000.0], [750000.0, 3400000.0], [725000.0, 3400000.0], [700000, 3400000], [700000.0, 3375000.0], [700000.0, 3350000.0], [700000.0, 3325000.0], [700000, 3300000]]
- projection :
- 32646
- s3 :
- s3://its-live-data/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.zarr
- skipped_granules :
- s3://its-live-data/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.json
- time_standard_img1 :
- UTC
- time_standard_img2 :
- UTC
- title :
- ITS_LIVE datacube of image pair velocities
- url :
- https://its-live-data.s3.amazonaws.com/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.zarr
Let’s take a look at the clipped raster alongside the vector outline. To start with and for the sake of easy visualizing we will take the mean of the magnitude of velocity variable along the mid_date dimension:
sample_glacier_raster_timemean = sample_glacier_raster.mean(dim='mid_date')
np.sqrt(sample_glacier_raster_timemean.vx**2 + sample_glacier_raster_timemean.vy**2).plot()
<matplotlib.collections.QuadMesh at 0x7f7f5d631650>
fig, ax = plt.subplots(figsize = (15,9))
sample_glacier_vec.plot(ax=ax, facecolor='none', edgecolor='red');
sample_glacier_raster.v.mean(dim=['mid_date']).plot(ax=ax);
Now let’s take a look at the x and y components of velocity, again averaging over time:
fig, axs = plt.subplots(ncols =2, figsize=(17,7))
sample_glacier_raster.vx.mean(dim='mid_date').plot(ax=axs[0]);
sample_glacier_raster.vy.mean(dim='mid_date').plot(ax=axs[1]);
sample_glacier_raster.v_error.mean(dim=['mid_date']).plot();
Exploring ITS_LIVE data#
ITS_LIVE data cubes come with many (53!) variables that carry information about the estimated surface velocities and the satellite images that were used to generate the surface velocity estimates. We won’t examine all of this information here but let’s look at a litte bit.
To start with, let’s look at the satellite imagery used to generate the velocity data.
We see that we have two data_vars that indicate which sensor that each image in the image pair at a certain time step comes from. We will “load” these values in to memory since we will use them later.
sample_glacier_raster.satellite_img2
<xarray.DataArray 'satellite_img2' (mid_date: 3974)>
array(['2B', '2B', '2B', ..., '8', '8', '7'], dtype=object)
Coordinates:
* mid_date (mid_date) datetime64[ns] 2018-04-14T04:18:49.171219968 ... 201...
mapping int64 0
Attributes:
description: id of the satellite that acquired image 2
standard_name: image2_satellite- mid_date: 3974
- '2B' '2B' '2B' '2A' '2A' '2B' '2B' ... '8' '8' '7' '7' '8' '8' '7'
array(['2B', '2B', '2B', ..., '8', '8', '7'], dtype=object)
- mid_date(mid_date)datetime64[ns]2018-04-14T04:18:49.171219968 .....
- description :
- midpoint of image 1 and image 2 acquisition date and time with granule's centroid longitude and latitude as microseconds
- standard_name :
- image_pair_center_date_with_time_separation
array(['2018-04-14T04:18:49.171219968', '2017-02-10T16:15:50.660901120', '2019-03-15T04:15:44.180925952', ..., '2018-06-11T04:10:57.953189888', '2017-05-27T04:10:08.145324032', '2017-05-07T04:11:30.865388288'], dtype='datetime64[ns]') - mapping()int640
- crs_wkt :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- WGS 84
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- WGS 84 / UTM zone 46N
- grid_mapping_name :
- transverse_mercator
- latitude_of_projection_origin :
- 0.0
- longitude_of_central_meridian :
- 93.0
- false_easting :
- 500000.0
- false_northing :
- 0.0
- scale_factor_at_central_meridian :
- 0.9996
- spatial_ref :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- GeoTransform :
- 700192.5 120.0 0.0 3394687.5 0.0 -120.0
array(0)
- mid_datePandasIndex
PandasIndex(DatetimeIndex(['2018-04-14 04:18:49.171219968', '2017-02-10 16:15:50.660901120', '2019-03-15 04:15:44.180925952', '2019-07-20 16:15:55.190603008', '2018-01-31 16:15:50.170811904', '2017-12-17 16:15:50.170508800', '2017-10-16 04:18:49.170811904', '2017-11-27 16:20:45.171105024', '2017-10-08 16:17:55.170906112', '2019-10-23 16:18:15.191001088', ... '2017-10-06 04:11:40.987761920', '2018-03-31 04:10:01.464065024', '2018-06-11 04:09:32.921265664', '2017-07-26 04:11:49.029760256', '2017-04-21 04:11:32.560144896', '2017-09-12 04:11:46.053865984', '2017-06-24 04:11:18.708142080', '2018-06-11 04:10:57.953189888', '2017-05-27 04:10:08.145324032', '2017-05-07 04:11:30.865388288'], dtype='datetime64[ns]', name='mid_date', length=3974, freq=None))
- description :
- id of the satellite that acquired image 2
- standard_name :
- image2_satellite
The satellite_img1 and satellite_img2 variables are 1-dimensional numpy arrays corresponding to the length of the mid_date dimension of the data cube. You can see that each element of the array is a string corresponding to a different satellite:
1A = Sentinel 1A, 1B = Sentinel 1B, 2A = Sentinel 2A
2B = Sentinel 2B, 8. = Landsat8 and 9. = Landsat9
Let’s re-arrange these string arrays into a format that is easier to work with.
First, we’ll make a set of all the different string values in the satellite image variables:
Examining velocity data from each satellite in ITS_LIVE dataset#
What if we only wanted to look at the velocity estimates from landat8?
l8_data = sample_glacier_raster.where(sample_glacier_raster['satellite_img1'] == '8', drop=True)
l8_data
<xarray.Dataset>
Dimensions: (mid_date: 662, y: 64, x: 73)
Coordinates:
* mid_date (mid_date) datetime64[ns] 2017-12-25T04:11:40...
* x (x) float64 7.003e+05 7.004e+05 ... 7.089e+05
* y (y) float64 3.395e+06 3.395e+06 ... 3.387e+06
mapping int64 0
Data variables: (12/59)
M11 (mid_date, y, x) float32 nan nan nan ... nan nan
M11_dr_to_vr_factor (mid_date) float32 nan nan nan ... nan nan nan
M12 (mid_date, y, x) float32 nan nan nan ... nan nan
M12_dr_to_vr_factor (mid_date) float32 nan nan nan ... nan nan nan
acquisition_date_img1 (mid_date) datetime64[ns] 2017-12-21T04:10:40...
acquisition_date_img2 (mid_date) datetime64[ns] 2017-12-29T04:12:40...
... ...
vy_error_modeled (mid_date) float32 1.163e+03 232.7 ... 166.2
vy_error_slow (mid_date) float32 112.5 37.6 54.1 ... 11.3 25.4
vy_error_stationary (mid_date) float32 112.5 37.6 54.2 ... 11.3 25.4
vy_stable_shift (mid_date) float32 -74.2 -25.7 ... -3.6 -10.8
vy_stable_shift_slow (mid_date) float32 -73.8 -25.7 ... -3.6 -10.7
vy_stable_shift_stationary (mid_date) float32 -74.2 -25.7 ... -3.6 -10.8
Attributes: (12/19)
Conventions: CF-1.8
GDAL_AREA_OR_POINT: Area
author: ITS_LIVE, a NASA MEaSUREs project (its-live.j...
autoRIFT_parameter_file: http://its-live-data.s3.amazonaws.com/autorif...
datacube_software_version: 1.0
date_created: 25-Sep-2023 22:00:23
... ...
s3: s3://its-live-data/datacubes/v2/N30E090/ITS_L...
skipped_granules: s3://its-live-data/datacubes/v2/N30E090/ITS_L...
time_standard_img1: UTC
time_standard_img2: UTC
title: ITS_LIVE datacube of image pair velocities
url: https://its-live-data.s3.amazonaws.com/datacu...- mid_date: 662
- y: 64
- x: 73
- mid_date(mid_date)datetime64[ns]2017-12-25T04:11:40.527109888 .....
- description :
- midpoint of image 1 and image 2 acquisition date and time with granule's centroid longitude and latitude as microseconds
- standard_name :
- image_pair_center_date_with_time_separation
array(['2017-12-25T04:11:40.527109888', '2018-12-12T04:08:03.179142912', '2018-12-04T04:08:17.320696064', ..., '2017-06-24T04:11:18.708142080', '2017-05-27T04:10:08.145324032', '2017-05-07T04:11:30.865388288'], dtype='datetime64[ns]') - x(x)float647.003e+05 7.004e+05 ... 7.089e+05
- description :
- x coordinate of projection
- standard_name :
- projection_x_coordinate
- axis :
- X
- long_name :
- x coordinate of projection
- units :
- metre
array([700252.5, 700372.5, 700492.5, 700612.5, 700732.5, 700852.5, 700972.5, 701092.5, 701212.5, 701332.5, 701452.5, 701572.5, 701692.5, 701812.5, 701932.5, 702052.5, 702172.5, 702292.5, 702412.5, 702532.5, 702652.5, 702772.5, 702892.5, 703012.5, 703132.5, 703252.5, 703372.5, 703492.5, 703612.5, 703732.5, 703852.5, 703972.5, 704092.5, 704212.5, 704332.5, 704452.5, 704572.5, 704692.5, 704812.5, 704932.5, 705052.5, 705172.5, 705292.5, 705412.5, 705532.5, 705652.5, 705772.5, 705892.5, 706012.5, 706132.5, 706252.5, 706372.5, 706492.5, 706612.5, 706732.5, 706852.5, 706972.5, 707092.5, 707212.5, 707332.5, 707452.5, 707572.5, 707692.5, 707812.5, 707932.5, 708052.5, 708172.5, 708292.5, 708412.5, 708532.5, 708652.5, 708772.5, 708892.5]) - y(y)float643.395e+06 3.395e+06 ... 3.387e+06
- description :
- y coordinate of projection
- standard_name :
- projection_y_coordinate
- axis :
- Y
- long_name :
- y coordinate of projection
- units :
- metre
array([3394627.5, 3394507.5, 3394387.5, 3394267.5, 3394147.5, 3394027.5, 3393907.5, 3393787.5, 3393667.5, 3393547.5, 3393427.5, 3393307.5, 3393187.5, 3393067.5, 3392947.5, 3392827.5, 3392707.5, 3392587.5, 3392467.5, 3392347.5, 3392227.5, 3392107.5, 3391987.5, 3391867.5, 3391747.5, 3391627.5, 3391507.5, 3391387.5, 3391267.5, 3391147.5, 3391027.5, 3390907.5, 3390787.5, 3390667.5, 3390547.5, 3390427.5, 3390307.5, 3390187.5, 3390067.5, 3389947.5, 3389827.5, 3389707.5, 3389587.5, 3389467.5, 3389347.5, 3389227.5, 3389107.5, 3388987.5, 3388867.5, 3388747.5, 3388627.5, 3388507.5, 3388387.5, 3388267.5, 3388147.5, 3388027.5, 3387907.5, 3387787.5, 3387667.5, 3387547.5, 3387427.5, 3387307.5, 3387187.5, 3387067.5]) - mapping()int640
- crs_wkt :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- WGS 84
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- WGS 84 / UTM zone 46N
- grid_mapping_name :
- transverse_mercator
- latitude_of_projection_origin :
- 0.0
- longitude_of_central_meridian :
- 93.0
- false_easting :
- 500000.0
- false_northing :
- 0.0
- scale_factor_at_central_meridian :
- 0.9996
- spatial_ref :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- GeoTransform :
- 700192.5 120.0 0.0 3394687.5 0.0 -120.0
array(0)
- M11(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- conversion matrix element (1st row, 1st column) that can be multiplied with vx to give range pixel displacement dr (see Eq. A18 in https://www.mdpi.com/2072-4292/13/4/749)
- grid_mapping :
- mapping
- standard_name :
- conversion_matrix_element_11
- units :
- pixel/(meter/year)
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - M11_dr_to_vr_factor(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- multiplicative factor that converts slant range pixel displacement dr to slant range velocity vr
- standard_name :
- M11_dr_to_vr_factor
- units :
- meter/(year*pixel)
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - M12(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- conversion matrix element (1st row, 2nd column) that can be multiplied with vy to give range pixel displacement dr (see Eq. A18 in https://www.mdpi.com/2072-4292/13/4/749)
- grid_mapping :
- mapping
- standard_name :
- conversion_matrix_element_12
- units :
- pixel/(meter/year)
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - M12_dr_to_vr_factor(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- multiplicative factor that converts slant range pixel displacement dr to slant range velocity vr
- standard_name :
- M12_dr_to_vr_factor
- units :
- meter/(year*pixel)
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - acquisition_date_img1(mid_date)datetime64[ns]2017-12-21T04:10:40.253580032 .....
- description :
- acquisition date and time of image 1
- standard_name :
- image1_acquition_date
array(['2017-12-21T04:10:40.253580032', '2018-11-22T04:10:24.234354944', '2018-11-22T04:10:24.234354944', '2017-02-04T04:10:29.099783936', '2018-01-22T04:10:27.510945024', '2018-11-22T04:10:24.234354944', '2017-01-19T04:10:36.447260928', '2017-02-04T04:10:29.099783936', '2017-11-03T04:10:45.832015872', '2017-11-03T04:10:45.832015872', '2017-02-04T04:10:29.099783936', '2017-12-21T04:10:40.253580032', '2018-11-22T04:10:24.234354944', '2018-01-22T04:10:27.510945024', '2018-11-22T04:10:24.234354944', '2017-12-21T04:10:40.253580032', '2017-02-04T04:10:29.099783936', '2017-01-19T04:10:36.447260928', '2018-01-22T04:10:27.510945024', '2017-01-19T04:10:36.447260928', '2017-02-04T04:10:29.099783936', '2017-02-04T04:10:29.099783936', '2018-01-22T04:10:27.510945024', '2017-11-03T04:10:45.832015872', '2017-11-03T04:10:45.832015872', '2018-12-08T04:10:21.702228992', '2017-02-04T04:10:29.099783936', '2018-01-22T04:10:27.510945024', '2016-10-31T04:10:49.197186048', '2018-01-22T04:10:27.510945024', '2016-10-31T04:10:49.197186048', '2017-01-19T04:10:36.447260928', '2018-12-08T04:10:21.702228992', '2017-01-19T04:10:36.447260928', '2017-12-21T04:10:40.253580032', '2017-11-03T04:10:45.832015872', '2017-12-21T04:10:40.253580032', '2017-01-19T04:10:36.447260928', '2018-01-22T04:10:27.510945024', '2019-01-09T04:10:19.605915904', ... '2017-07-30T04:10:25.156854016', '2017-07-30T04:10:25.156854016', '2017-07-30T04:10:25.156854016', '2017-07-30T04:10:25.156854016', '2018-02-07T04:10:19.247780096', '2016-11-16T04:10:48.428282112', '2016-10-15T04:10:47.896870912', '2017-07-30T04:10:25.156854016', '2018-03-27T04:09:57.437323008', '2017-07-30T04:10:25.156854016', '2017-04-09T04:09:59.003422976', '2018-02-07T04:10:19.247780096', '2017-04-09T04:09:59.003422976', '2016-10-15T04:10:47.896870912', '2017-07-30T04:10:25.156854016', '2017-07-30T04:10:25.156854016', '2017-07-30T04:10:25.156854016', '2017-09-16T04:10:35.331774976', '2017-10-18T04:10:46.076395008', '2017-07-30T04:10:25.156854016', '2016-10-15T04:10:47.896870912', '2017-11-19T04:10:41.686725376', '2017-04-09T04:09:59.003422976', '2018-05-30T04:09:17.034597888', '2017-04-09T04:09:59.003422976', '2017-07-14T04:10:16.946407936', '2017-04-09T04:09:59.003422976', '2017-09-16T04:10:35.331774976', '2017-07-30T04:10:25.156854016', '2018-05-14T04:09:29.903631104', '2017-09-16T04:10:35.331774976', '2017-09-16T04:10:35.331774976', '2017-12-05T04:10:37.029957888', '2018-04-28T04:09:39.925913088', '2017-07-30T04:10:25.156854016', '2016-10-15T04:10:47.896870912', '2017-04-09T04:09:59.003422976', '2017-04-09T04:09:59.003422976'], dtype='datetime64[ns]') - acquisition_date_img2(mid_date)datetime64[ns]2017-12-29T04:12:40.458198016 .....
- description :
- acquisition date and time of image 2
- standard_name :
- image2_acquition_date
array(['2017-12-29T04:12:40.458198016', '2019-01-01T04:05:41.761686272', '2018-12-16T04:06:10.044793088', '2017-12-29T04:12:40.458198016', '2019-01-01T04:05:41.761686272', '2020-02-13T04:10:30.639724032', '2017-01-27T04:12:29.455911936', '2018-01-22T04:10:27.510945024', '2017-11-11T04:13:04.720666112', '2017-12-29T04:12:40.458198016', '2018-02-15T04:11:59.198033920', '2019-01-01T04:05:41.761686272', '2019-01-17T04:05:11.586401024', '2018-12-16T04:06:10.044793088', '2018-11-30T04:06:36.228204288', '2018-12-16T04:06:10.044793088', '2017-12-21T04:10:40.253580032', '2017-12-29T04:12:40.458198016', '2018-02-15T04:11:59.198033920', '2018-01-22T04:10:27.510945024', '2017-11-11T04:13:04.720666112', '2017-02-28T04:12:32.528041984', '2018-11-22T04:10:24.234354944', '2018-01-22T04:10:27.510945024', '2017-12-21T04:10:40.253580032', '2019-01-01T04:05:41.761686272', '2017-11-03T04:10:45.832015872', '2019-06-02T04:10:12.332978176', '2017-11-11T04:13:04.720666112', '2019-01-17T04:05:11.586401024', '2017-12-29T04:12:40.458198016', '2017-12-21T04:10:40.253580032', '2018-12-16T04:06:10.044793088', '2018-02-15T04:11:59.198033920', '2019-06-02T04:10:12.332978176', '2019-01-01T04:05:41.761686272', '2018-02-15T04:11:59.198033920', '2017-02-28T04:12:32.528041984', '2018-11-30T04:06:36.228204288', '2020-02-29T04:10:26.243158016', ... '2017-11-19T04:10:41.686725376', '2018-05-30T04:09:17.034597888', '2018-01-30T04:12:11.667300096', '2018-04-04T04:11:23.527504896', '2018-03-03T04:11:49.197383936', '2018-03-03T04:11:49.197383936', '2017-06-04T04:13:02.386535936', '2018-11-30T04:06:36.228204288', '2018-07-25T04:09:25.555763200', '2018-05-22T04:10:35.049019904', '2018-05-22T04:10:35.049019904', '2018-10-29T04:07:21.963168256', '2017-10-26T04:13:06.609417984', '2017-04-09T04:09:59.003422976', '2019-01-25T04:10:15.711925760', '2018-01-14T04:12:27.084400896', '2019-01-09T04:10:19.605915904', '2017-10-26T04:13:06.609417984', '2018-03-03T04:11:49.197383936', '2018-07-25T04:09:25.555763200', '2017-07-14T04:10:16.946407936', '2018-07-25T04:09:25.555763200', '2018-03-03T04:11:49.197383936', '2018-07-25T04:09:25.555763200', '2018-09-19T04:10:06.348390144', '2017-10-26T04:13:06.609417984', '2017-09-16T04:10:35.331774976', '2018-11-30T04:06:36.228204288', '2018-10-29T04:07:21.963168256', '2018-07-25T04:09:25.555763200', '2018-10-29T04:07:21.963168256', '2018-03-03T04:11:49.197383936', '2018-07-25T04:09:25.555763200', '2018-07-25T04:09:25.555763200', '2017-10-26T04:13:06.609417984', '2018-03-03T04:11:49.197383936', '2017-07-14T04:10:16.946407936', '2017-06-04T04:13:02.386535936'], dtype='datetime64[ns]') - autoRIFT_software_version(mid_date)object'1.5.0' '1.5.0' ... '1.5.0' '1.5.0'
- description :
- version of autoRIFT software
- standard_name :
- autoRIFT_software_version
array(['1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', ... '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0'], dtype=object) - chip_size_height(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- chip_size_coordinates :
- Optical data: chip_size_coordinates = 'image projection geometry: width = x, height = y'. Radar data: chip_size_coordinates = 'radar geometry: width = range, height = azimuth'
- description :
- height of search template (chip)
- grid_mapping :
- mapping
- standard_name :
- chip_size_height
- units :
- m
- y_pixel_size :
- 10.0
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - chip_size_width(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- chip_size_coordinates :
- Optical data: chip_size_coordinates = 'image projection geometry: width = x, height = y'. Radar data: chip_size_coordinates = 'radar geometry: width = range, height = azimuth'
- description :
- width of search template (chip)
- grid_mapping :
- mapping
- standard_name :
- chip_size_width
- units :
- m
- x_pixel_size :
- 10.0
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - date_center(mid_date)datetime64[ns]2017-12-25T04:11:40.355888896 .....
- description :
- midpoint of image 1 and image 2 acquisition date
- standard_name :
- image_pair_center_date
array(['2017-12-25T04:11:40.355888896', '2018-12-12T04:08:02.998021120', '2018-12-04T04:08:17.139574016', '2017-07-18T04:11:34.778990848', '2018-07-13T04:08:04.636314880', '2019-07-04T04:10:27.437039104', '2017-01-23T04:11:32.951587072', '2017-07-30T04:10:28.305363968', '2017-11-07T04:11:55.276340992', '2017-12-01T04:11:43.145106944', '2017-08-11T04:11:14.148909056', '2018-06-27T04:08:11.007632896', '2018-12-20T04:07:47.910377984', '2018-07-05T04:08:18.777868800', '2018-11-26T04:08:30.231279104', '2018-06-19T04:08:25.149186048', '2017-07-14T04:10:34.676681984', '2017-07-10T04:11:38.452729088', '2018-02-03T04:11:13.354489088', '2017-07-22T04:10:31.979102976', '2017-06-24T04:11:46.910224896', '2017-02-16T04:11:30.813913088', '2018-06-23T04:10:25.872649728', '2017-12-13T04:10:36.671480064', '2017-11-27T04:10:43.042798080', '2018-12-20T04:08:01.731956992', '2017-06-20T04:10:37.465900032', '2018-09-27T04:10:19.921960960', '2017-05-07T04:11:56.958926336', '2018-07-21T04:07:49.548673024', '2017-05-31T04:11:44.827692032', '2017-07-06T04:10:38.350421248', '2018-12-12T04:08:15.873510912', '2017-08-03T04:11:17.822647296', '2018-09-11T04:10:26.293278976', '2018-06-03T04:08:13.796850944', '2018-01-18T04:11:19.725807104', '2017-02-08T04:11:34.487651328', '2018-06-27T04:08:31.869574912', '2019-08-05T04:10:22.924537088', ... '2017-09-24T04:10:33.421789952', '2017-12-29T04:09:51.095726336', '2017-10-30T04:11:18.412077056', '2017-12-01T04:10:54.342180096', '2018-02-19T04:11:04.222582016', '2017-07-10T04:11:18.812833024', '2017-02-08T04:11:55.141702912', '2018-03-31T04:08:30.692528640', '2018-05-26T04:09:41.496542976', '2017-12-25T04:10:30.102937088', '2017-10-30T04:10:17.026221056', '2018-06-19T04:08:50.605474048', '2017-07-18T04:11:32.806420992', '2017-01-11T04:10:23.450147072', '2018-04-28T04:10:20.434390016', '2017-10-22T04:11:26.120627968', '2018-04-20T04:10:22.381384960', '2017-10-06T04:11:50.970597120', '2017-12-25T04:11:17.636889344', '2018-01-26T04:09:55.356307968', '2017-02-28T04:10:32.421638912', '2018-03-23T04:10:03.621243904', '2017-09-20T04:10:54.100402944', '2018-06-27T04:09:21.295180032', '2017-12-29T04:10:02.675906816', '2017-09-04T04:11:41.777913344', '2017-06-28T04:10:17.167599104', '2018-04-24T04:08:35.779988992', '2018-03-15T04:08:53.560011008', '2018-06-19T04:09:27.729697024', '2018-04-08T04:08:58.647471104', '2017-12-09T04:11:12.264579072', '2018-03-31T04:10:01.292859904', '2018-06-11T04:09:32.740837888', '2017-09-12T04:11:45.883136000', '2017-06-24T04:11:18.547127040', '2017-05-27T04:10:07.974915072', '2017-05-07T04:11:30.694979072'], dtype='datetime64[ns]') - date_dt(mid_date)timedelta64[ns]8 days 00:02:00.217895504 ... 56...
- description :
- time separation between acquisition of image 1 and image 2
- standard_name :
- image_pair_time_separation
array([ 691320217895504, 3455717541503909, 2073345886230468, 28339331835937495, 29721315234375000, 38707205273437495, 691313049316405, 30412797363281252, 691338922119144, 4838514697265621, 32486489648437495, 32486102050781252, 4838087219238279, 28338941601562504, 690972006225585, 31103731054687495, 27648010546875000, 29721723925781252, 2073691625976558, 31795192089843747, 24192155566406252, 2073723431396486, 26265597363281252, 6911981542968747, 4147194396972657, 2073320013427738, 23500815820312504, 42854384179687495, 32486534472656252, 31103683593750000, 36633710742187495, 29030402636718747, 690948358154297, 33868881738281252, 45619173632812504, 36633296777343747, 4838479101562504, 3456116015625000, 26956567968750000, 35942407910156252, 34560010546875000, 40780871191406252, 38707178906250000, 37324807910156252, 24883210546875000, 33177578906250000, 35250923144531252, 31795221093750000, 33868549511718747, 25574547656250000, 20736026367187495, 35942368359375000, 8985673168945315, 33868470410156252, 35251268554687495, 29721354785156252, 3455689855957027, 26956942382812504, 690891998291017, 29030423730468747, ... 8985667236328126, 20735968359375000, 35942357812500000, 12441626367187495, 15897730517578126, 29030386816406252, 25574175878906252, 46310088867187495, 11750546337890621, 19353581542968747, 26265621093750000, 45619294921875000, 16588856689453126, 14515314697265621, 24192147656250000, 24883163085937495, 17280134472656252, 38016065917968747, 20735972314453126, 42854397363281252, 11059211865234378, 9676816479492189, 26265531445312504, 15897706787109378, 21427258007812504, 2073689978027342, 40780860644531252, 20044934472656252, 42162970605468747, 10367968359375000, 25574410546875000, 35251236914062504, 22809423339843747, 17280187207031252, 15206351220703126, 47001589453125000, 14515321289062504, 45619194726562504, 3456151281738279, 11750463281250000, 31103939355468747, 23500768359375000, 21427123535156252, 28339310742187495, 4838408569335936, 45619205273437495, 8985769409179684, 13824036914062504, 38015760058593747, 39398218066406252, 6220795385742189, 35251007519531252, 14515273828125000, 20044728808593747, 7603185498046873, 7603361499023441, 43545660644531252, 8294417797851558, 4838583251953126], dtype='timedelta64[ns]') - floatingice(y, x, mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- floating ice mask, 0 = non-floating-ice, 1 = floating-ice
- flag_meanings :
- non-ice ice
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- floating ice mask
- url :
- https://its-live-data.s3.amazonaws.com/autorift_parameters/v001/N46_0120m_floatingice.tif
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - granule_url(mid_date)object'https://its-live-data.s3.amazon...
- description :
- original granule URL
- standard_name :
- granule_url
array(['https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20171221_20200902_02_T1_X_LE07_L1TP_135039_20171229_20200830_02_T1_G0120V02_P099.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20181122_20200830_02_T1_X_LE07_L1TP_135039_20190101_20200827_02_T1_G0120V02_P099.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20181122_20200830_02_T1_X_LE07_L1TP_135039_20181216_20200827_02_T1_G0120V02_P098.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170204_20200905_02_T1_X_LE07_L1TP_135039_20171229_20200830_02_T1_G0120V02_P096.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20180122_20200902_02_T1_X_LE07_L1TP_135039_20190101_20200827_02_T1_G0120V02_P094.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20181122_20200830_02_T1_X_LC08_L1TP_135039_20200213_20200823_02_T1_G0120V02_P094.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170119_20200905_02_T1_X_LE07_L1TP_135039_20170127_20201008_02_T1_G0120V02_P094.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170204_20200905_02_T1_X_LC08_L1TP_135039_20180122_20200902_02_T1_G0120V02_P093.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20171103_20200902_02_T1_X_LE07_L1TP_135039_20171111_20200830_02_T1_G0120V02_P092.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20171103_20200902_02_T1_X_LE07_L1TP_135039_20171229_20200830_02_T1_G0120V02_P091.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170204_20200905_02_T1_X_LE07_L1TP_135039_20180215_20200829_02_T1_G0120V02_P092.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20171221_20200902_02_T1_X_LE07_L1TP_135039_20190101_20200827_02_T1_G0120V02_P091.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20181122_20200830_02_T1_X_LE07_L1TP_135039_20190117_20200827_02_T1_G0120V02_P091.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20180122_20200902_02_T1_X_LE07_L1TP_135039_20181216_20200827_02_T1_G0120V02_P091.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20181122_20200830_02_T1_X_LE07_L1TP_135039_20181130_20200827_02_T1_G0120V02_P090.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20171221_20200902_02_T1_X_LE07_L1TP_135039_20181216_20200827_02_T1_G0120V02_P089.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170204_20200905_02_T1_X_LC08_L1TP_135039_20171221_20200902_02_T1_G0120V02_P089.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170119_20200905_02_T1_X_LE07_L1TP_135039_20171229_20200830_02_T1_G0120V02_P089.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20180122_20200902_02_T1_X_LE07_L1TP_135039_20180215_20200829_02_T1_G0120V02_P088.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170119_20200905_02_T1_X_LC08_L1TP_135039_20180122_20200902_02_T1_G0120V02_P088.nc', ... 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170730_20200903_02_T1_X_LE07_L1TP_135039_20180725_20200828_02_T1_G0120V02_P008.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20161015_20200905_02_T1_X_LC08_L1TP_135039_20170714_20200903_02_T1_G0120V02_P007.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20171119_20200902_02_T1_X_LE07_L1TP_135039_20180725_20200828_02_T1_G0120V02_P008.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170409_20200904_02_T1_X_LE07_L1TP_135039_20180303_20200829_02_T1_G0120V02_P007.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20180530_20200831_02_T1_X_LE07_L1TP_135039_20180725_20200828_02_T1_G0120V02_P007.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170409_20200904_02_T1_X_LC08_L1TP_135039_20180919_20200830_02_T1_G0120V02_P006.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170714_20200903_02_T1_X_LE07_L1TP_135039_20171026_20200830_02_T1_G0120V02_P007.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170409_20200904_02_T1_X_LC08_L1TP_135039_20170916_20200903_02_T1_G0120V02_P007.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170916_20200903_02_T1_X_LE07_L1TP_135039_20181130_20200827_02_T1_G0120V02_P007.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N20E090/LC08_L1TP_135039_20170730_20200903_02_T1_X_LE07_L1TP_135039_20181029_20200827_02_T1_G0120V02_P007.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20180514_20200901_02_T1_X_LE07_L1TP_135039_20180725_20200828_02_T1_G0120V02_P006.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170916_20200903_02_T1_X_LE07_L1TP_135039_20181029_20200827_02_T1_G0120V02_P005.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170916_20200903_02_T1_X_LE07_L1TP_135039_20180303_20200829_02_T1_G0120V02_P004.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20171205_20200902_02_T1_X_LE07_L1TP_135039_20180725_20200828_02_T1_G0120V02_P005.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20180428_20200901_02_T1_X_LE07_L1TP_135039_20180725_20200828_02_T1_G0120V02_P003.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170730_20200903_02_T1_X_LE07_L1TP_135039_20171026_20200830_02_T1_G0120V02_P003.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20161015_20200905_02_T1_X_LE07_L1TP_135039_20180303_20200829_02_T1_G0120V02_P003.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170409_20200904_02_T1_X_LC08_L1TP_135039_20170714_20200903_02_T1_G0120V02_P003.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170409_20200904_02_T1_X_LE07_L1TP_135039_20170604_20200831_02_T1_G0120V02_P002.nc'], dtype=object) - interp_mask(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- light interpolation mask
- flag_meanings :
- measured interpolated
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- interpolated_value_mask
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - landice(y, x, mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- land ice mask, 0 = non-land-ice, 1 = land-ice
- flag_meanings :
- non-ice ice
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- land ice mask
- url :
- https://its-live-data.s3.amazonaws.com/autorift_parameters/v001/N46_0120m_landice.tif
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - mission_img1(mid_date)object'L' 'L' 'L' 'L' ... 'L' 'L' 'L' 'L'
- description :
- id of the mission that acquired image 1
- standard_name :
- image1_mission
array(['L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', ... 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L'], dtype=object) - mission_img2(mid_date)object'L' 'L' 'L' 'L' ... 'L' 'L' 'L' 'L'
- description :
- id of the mission that acquired image 2
- standard_name :
- image2_mission
array(['L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', ... 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L'], dtype=object) - roi_valid_percentage(mid_date)float3299.0 99.0 98.0 96.0 ... 3.9 3.2 2.0
- description :
- percentage of pixels with a valid velocity estimate determined for the intersection of the full image pair footprint and the region of interest (roi) that defines where autoRIFT tried to estimate a velocity
- standard_name :
- region_of_interest_valid_pixel_percentage
array([99. , 99. , 98. , 96. , 94.8, 94.3, 94. , 93.2, 92. , 91.5, 92. , 91.6, 91. , 91.4, 90. , 89.1, 89.3, 89.2, 88.1, 88.1, 86.9, 87. , 86.3, 86.1, 86.1, 86. , 86.4, 85.8, 85. , 84.6, 83.6, 83.7, 84. , 84.3, 82.8, 81.9, 81.6, 82. , 80.5, 80.5, 80.7, 81.1, 80.6, 79.8, 79.6, 80.1, 80.3, 78.5, 78.5, 79.1, 78.9, 77.7, 78. , 78.4, 77.3, 77.4, 76.4, 75.7, 74.7, 73.7, 73.6, 74.3, 73.6, 73.7, 73. , 73.4, 72.8, 72.6, 71.7, 71.8, 71.9, 71.8, 71.4, 70.9, 71.2, 70.7, 71.4, 69.7, 70.3, 70. , 69.6, 68.8, 69.2, 68.6, 69. , 67.7, 68.3, 68.3, 67.6, 67. , 66.5, 66.9, 67. , 66.8, 67.3, 65.6, 66. , 66.3, 66. , 65.7, 65.6, 65.4, 65.4, 64.6, 65.3, 65.4, 65. , 63.6, 63.8, 64. , 64.3, 63.5, 63.6, 63.3, 63.1, 62.5, 62.8, 62.6, 62.1, 62. , 60.7, 60.7, 61.3, 61.2, 61.1, 59.6, 60.4, 59.9, 60.1, 59.3, 58.6, 59.2, 59. , 58.6, 59.4, 58.9, 58.8, 59.2, 57.7, 58.1, 57.6, 57.6, 57.8, 58.4, 57.4, 56.8, 56.8, 56. , 56. , 55.6, 56.3, 55.8, 55.4, 55. , 55.4, 54.6, 54.3, 54.2, 54.3, 54.4, 53.4, 52.9, 53.1, 53. , 52.5, 52.7, 52.5, 51.9, 52.1, 52. , 52.1, 52.1, 52. , 51.5, 50.5, 51.4, 50.2, 49.5, 49.4, 49.3, 49.2, 48. , 48.2, 47.8, 48. , 48.2, 48. , 47. , 46.6, 46.5, 47.2, 46.7, 46.8, 47.3, 46.9, 47. , 47. , 46.9, 47.4, 46.1, 46.2, 45.8, 45.9, 44.8, 44.5, 44.6, 44.8, 44.6, 44.5, 43.5, 44. , 44.1, 44.4, 44. , 43.4, 43. , 43.3, 42.5, 42.6, 42.7, ... 22.7, 23.2, 23.4, 22.7, 22.8, 23. , 22.6, 23.4, 22.6, 22.7, 23.2, 22.8, 21.9, 22. , 22.2, 21.5, 21.6, 22.2, 22.3, 22.3, 21.5, 22.4, 22.2, 21.7, 22. , 21.7, 21.8, 22.1, 21.9, 21.5, 22.4, 22.3, 20.8, 21.2, 20.7, 20.9, 21.4, 20.8, 21. , 20.6, 20.8, 20.7, 21.2, 21. , 20.6, 20.8, 21.1, 20.5, 20.9, 20.7, 19.8, 19.5, 19.9, 19.9, 20. , 20.4, 19.9, 19.5, 20.1, 19.9, 20.3, 20.4, 20.2, 19.5, 19.6, 19.9, 20.4, 19.6, 19.3, 19.4, 18.7, 18.5, 19.4, 19.4, 18.8, 18.9, 19. , 19.1, 19. , 18.8, 18.6, 19. , 19.1, 19.1, 19.1, 18.9, 18.2, 18.1, 17.8, 17.5, 18.4, 18.4, 17.5, 18. , 18.3, 17.5, 17.7, 17.7, 17.1, 16.7, 16.6, 16.7, 17.1, 17.1, 16.5, 17. , 16.8, 17.4, 16.6, 15.5, 15.8, 16. , 15.9, 15.6, 15.7, 16.3, 16. , 15.8, 15.6, 15.7, 16.3, 16.3, 16. , 15.5, 14.7, 14.9, 15.4, 14.8, 15.2, 14.9, 14.8, 14.5, 15.3, 13.5, 13.8, 13.7, 13.6, 14.4, 14.1, 14.1, 13.6, 13.9, 13.6, 14. , 14.3, 14.2, 14.1, 14. , 12.8, 12.9, 12.9, 12.7, 12.5, 12.9, 13.1, 12.4, 11.6, 11.9, 12.4, 12.2, 11.5, 11.5, 11.7, 10.8, 10.5, 10.5, 11.2, 11.2, 11.3, 11. , 10.2, 10.3, 10. , 9.8, 9.7, 10.3, 9.7, 10.4, 9.7, 8.8, 9.3, 9.1, 8.5, 8.8, 8.8, 9.4, 8.9, 8.3, 8.4, 8.3, 8.2, 7.7, 8.1, 7.6, 8.2, 7.4, 7.2, 6.8, 7.2, 7. , 7.2, 7.4, 6.3, 5.2, 4.9, 5.2, 3.6, 3.7, 3.9, 3.2, 2. ], dtype=float32) - satellite_img1(mid_date)object'8' '8' '8' '8' ... '8' '8' '8' '8'
- description :
- id of the satellite that acquired image 1
- standard_name :
- image1_satellite
array(['8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', ... '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8'], dtype=object) - satellite_img2(mid_date)object'7' '7' '7' '7' ... '7' '7' '8' '7'
- description :
- id of the satellite that acquired image 2
- standard_name :
- image2_satellite
array(['7', '7', '7', '7', '7', '8', '7', '8', '7', '7', '7', '7', '7', '7', '7', '7', '8', '7', '7', '8', '7', '7', '8', '8', '8', '7', '8', '8', '7', '7', '7', '8', '7', '7', '8', '7', '7', '7', '7', '8', '8', '7', '8', '8', '8', '8', '7', '8', '7', '7', '8', '8', '7', '7', '7', '7', '7', '7', '7', '8', '8', '7', '7', '8', '8', '8', '8', '8', '7', '7', '8', '7', '7', '7', '8', '8', '8', '7', '7', '7', '8', '8', '8', '8', '7', '7', '7', '8', '8', '7', '7', '7', '7', '8', '8', '7', '7', '8', '7', '8', '7', '7', '8', '7', '8', '8', '8', '8', '7', '7', '8', '8', '7', '8', '8', '8', '8', '8', '7', '7', '8', '8', '7', '8', '8', '8', '8', '7', '8', '7', '7', '7', '7', '8', '8', '8', '8', '8', '7', '7', '8', '7', '8', '7', '8', '7', '8', '7', '7', '7', '8', '7', '8', '7', '8', '7', '8', '7', '8', '8', '8', '8', '8', '7', '7', '7', '8', '7', '8', '7', '7', '7', '8', '8', '8', '8', '8', '8', '7', '7', '7', '7', '8', '8', '8', '8', '7', '8', '7', '8', '7', '7', '8', '8', '7', '7', '7', '8', '7', '7', '8', '8', '8', '8', '8', '7', '7', '8', '7', '7', '8', '7', '7', '8', '7', '7', '7', '8', '7', '7', '8', '8', '7', '8', '7', '7', '8', '8', '7', '8', '7', '8', '8', '8', '8', '7', '7', '8', '8', '7', '8', '7', '7', '7', '8', '8', '8', '8', '8', '7', '7', '8', '8', '8', '8', '7', '8', '7', '8', '8', ... '7', '7', '7', '8', '8', '7', '8', '8', '7', '8', '7', '8', '7', '8', '7', '7', '8', '7', '8', '8', '7', '7', '7', '7', '7', '7', '8', '8', '7', '7', '7', '7', '7', '8', '8', '7', '8', '7', '8', '8', '7', '7', '7', '8', '8', '8', '7', '7', '8', '8', '8', '8', '8', '7', '8', '8', '7', '7', '8', '8', '8', '8', '7', '8', '8', '8', '8', '7', '7', '8', '7', '8', '7', '7', '8', '8', '8', '7', '7', '8', '8', '8', '7', '8', '7', '8', '7', '7', '7', '7', '8', '7', '7', '7', '7', '8', '8', '7', '8', '7', '7', '8', '7', '7', '8', '8', '7', '7', '7', '8', '7', '8', '7', '7', '7', '7', '7', '7', '7', '8', '7', '7', '8', '8', '7', '8', '8', '7', '7', '8', '7', '8', '8', '8', '7', '8', '7', '8', '7', '8', '7', '7', '8', '7', '7', '8', '7', '7', '8', '7', '8', '7', '7', '8', '7', '7', '7', '7', '7', '8', '7', '7', '7', '7', '7', '7', '7', '8', '7', '7', '8', '7', '8', '7', '8', '8', '7', '8', '8', '7', '7', '7', '7', '7', '7', '7', '8', '7', '8', '8', '8', '7', '8', '7', '7', '7', '8', '8', '8', '8', '7', '7', '8', '7', '7', '8', '8', '8', '8', '8', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '8', '8', '7', '8', '7', '7', '7', '8', '7', '7', '7', '8', '7', '8', '7', '7', '7', '7', '7', '7', '7', '7', '7', '8', '7'], dtype=object) - sensor_img1(mid_date)object'C' 'C' 'C' 'C' ... 'C' 'C' 'C' 'C'
- description :
- id of the sensor that acquired image 1
- standard_name :
- image1_sensor
array(['C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', ... 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C'], dtype=object) - sensor_img2(mid_date)object'E' 'E' 'E' 'E' ... 'E' 'E' 'C' 'E'
- description :
- id of the sensor that acquired image 2
- standard_name :
- image2_sensor
array(['E', 'E', 'E', 'E', 'E', 'C', 'E', 'C', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'C', 'E', 'E', 'C', 'E', 'E', 'C', 'C', 'C', 'E', 'C', 'C', 'E', 'E', 'E', 'C', 'E', 'E', 'C', 'E', 'E', 'E', 'E', 'C', 'C', 'E', 'C', 'C', 'C', 'C', 'E', 'C', 'E', 'E', 'C', 'C', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'C', 'C', 'E', 'E', 'C', 'C', 'C', 'C', 'C', 'E', 'E', 'C', 'E', 'E', 'E', 'C', 'C', 'C', 'E', 'E', 'E', 'C', 'C', 'C', 'C', 'E', 'E', 'E', 'C', 'C', 'E', 'E', 'E', 'E', 'C', 'C', 'E', 'E', 'C', 'E', 'C', 'E', 'E', 'C', 'E', 'C', 'C', 'C', 'C', 'E', 'E', 'C', 'C', 'E', 'C', 'C', 'C', 'C', 'C', 'E', 'E', 'C', 'C', 'E', 'C', 'C', 'C', 'C', 'E', 'C', 'E', 'E', 'E', 'E', 'C', 'C', 'C', 'C', 'C', 'E', 'E', 'C', 'E', 'C', 'E', 'C', 'E', 'C', 'E', 'E', 'E', 'C', 'E', 'C', 'E', 'C', 'E', 'C', 'E', 'C', 'C', 'C', 'C', 'C', 'E', 'E', 'E', 'C', 'E', 'C', 'E', 'E', 'E', 'C', 'C', 'C', 'C', 'C', 'C', 'E', 'E', 'E', 'E', 'C', 'C', 'C', 'C', 'E', 'C', 'E', 'C', 'E', 'E', 'C', 'C', 'E', 'E', 'E', 'C', 'E', 'E', 'C', 'C', 'C', 'C', 'C', 'E', 'E', 'C', 'E', 'E', 'C', 'E', 'E', 'C', 'E', 'E', 'E', 'C', 'E', 'E', 'C', 'C', 'E', 'C', 'E', 'E', 'C', 'C', 'E', 'C', 'E', 'C', 'C', 'C', 'C', 'E', 'E', 'C', 'C', 'E', 'C', 'E', 'E', 'E', 'C', 'C', 'C', 'C', 'C', 'E', 'E', 'C', 'C', 'C', 'C', 'E', 'C', 'E', 'C', 'C', ... 'E', 'E', 'E', 'C', 'C', 'E', 'C', 'C', 'E', 'C', 'E', 'C', 'E', 'C', 'E', 'E', 'C', 'E', 'C', 'C', 'E', 'E', 'E', 'E', 'E', 'E', 'C', 'C', 'E', 'E', 'E', 'E', 'E', 'C', 'C', 'E', 'C', 'E', 'C', 'C', 'E', 'E', 'E', 'C', 'C', 'C', 'E', 'E', 'C', 'C', 'C', 'C', 'C', 'E', 'C', 'C', 'E', 'E', 'C', 'C', 'C', 'C', 'E', 'C', 'C', 'C', 'C', 'E', 'E', 'C', 'E', 'C', 'E', 'E', 'C', 'C', 'C', 'E', 'E', 'C', 'C', 'C', 'E', 'C', 'E', 'C', 'E', 'E', 'E', 'E', 'C', 'E', 'E', 'E', 'E', 'C', 'C', 'E', 'C', 'E', 'E', 'C', 'E', 'E', 'C', 'C', 'E', 'E', 'E', 'C', 'E', 'C', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'C', 'E', 'E', 'C', 'C', 'E', 'C', 'C', 'E', 'E', 'C', 'E', 'C', 'C', 'C', 'E', 'C', 'E', 'C', 'E', 'C', 'E', 'E', 'C', 'E', 'E', 'C', 'E', 'E', 'C', 'E', 'C', 'E', 'E', 'C', 'E', 'E', 'E', 'E', 'E', 'C', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'C', 'E', 'E', 'C', 'E', 'C', 'E', 'C', 'C', 'E', 'C', 'C', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'C', 'E', 'C', 'C', 'C', 'E', 'C', 'E', 'E', 'E', 'C', 'C', 'C', 'C', 'E', 'E', 'C', 'E', 'E', 'C', 'C', 'C', 'C', 'C', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'C', 'C', 'E', 'C', 'E', 'E', 'E', 'C', 'E', 'E', 'E', 'C', 'E', 'C', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'C', 'E'], dtype=object) - stable_count_slow(mid_date)float646.304e+04 6.037e+04 ... 3.688e+04
- description :
- number of valid pixels over slowest 25% of ice
- standard_name :
- stable_count_slow
- units :
- count
array([63035., 60373., 12343., 43082., 26491., 41111., 5234., 24156., 47472., 13668., 22255., 49070., 11254., 35948., 60149., 5853., 1344., 61020., 62075., 38755., 20004., 424., 9003., 41705., 61020., 64087., 2841., 7868., 57652., 59507., 34883., 24203., 33517., 33987., 16150., 28827., 37578., 44729., 27785., 32064., 46694., 34529., 21574., 25079., 9514., 8015., 8031., 59955., 23049., 31137., 51235., 28297., 27069., 34225., 13281., 56023., 23842., 28060., 3054., 1900., 58830., 53653., 7165., 18550., 837., 13570., 60550., 35035., 42190., 45460., 59604., 30918., 51360., 11801., 16620., 36272., 27701., 13951., 16316., 59570., 58244., 35443., 64503., 27244., 17355., 1033., 59833., 14269., 58196., 34335., 31096., 17376., 41960., 23150., 65147., 7167., 15968., 51774., 47622., 44522., 65002., 7610., 31988., 45997., 37338., 43251., 33428., 6550., 32017., 10284., 17732., 331., 28831., 63337., 40266., 7611., 59878., 62832., 6638., 34323., 65115., 9267., 63444., 29687., 24507., 24201., 63105., 29168., 28008., 206., 32203., 30702., 58734., 20705., 11115., 59811., 41530., 37826., 52639., 63734., 45659., 16863., 13621., 30455., 499., 13107., 7792., 7019., 47502., 53152., 59775., 37539., 40859., 54742., 56060., 21825., 28260., 3769., 13957., 62151., ... 10672., 22941., 25814., 31612., 17666., 24056., 34373., 26102., 28616., 28178., 45737., 26513., 33471., 56429., 17951., 21749., 13671., 58606., 4961., 20377., 23440., 36254., 12754., 36856., 11180., 17468., 14532., 64600., 6912., 14823., 15753., 60817., 91., 60269., 39126., 35025., 55769., 8743., 29328., 50861., 1140., 21479., 55823., 18826., 45835., 16928., 35408., 18706., 37431., 22255., 39943., 7006., 30998., 34389., 34800., 37857., 16363., 3370., 10762., 24777., 17802., 22717., 49088., 25460., 23318., 52591., 24147., 34095., 31210., 45471., 10050., 46735., 3922., 8560., 2283., 7899., 6590., 4402., 1580., 36763., 48007., 53991., 25463., 45877., 31006., 49171., 33808., 14079., 50711., 16674., 16505., 42561., 62449., 57698., 52210., 32016., 38178., 38618., 4528., 29653., 5548., 9857., 42546., 4101., 47325., 8395., 24288., 6025., 36064., 48022., 20782., 11596., 59693., 6552., 9688., 8746., 3430., 46778., 20340., 54888., 4175., 42428., 48928., 44147., 55754., 46092., 29312., 35464., 23887., 22110., 29426., 25222., 36564., 53833., 43041., 18602., 43977., 12535., 8458., 5600., 15194., 16590., 3313., 54030., 10567., 57964., 16440., 62997., 2114., 46046., 27250., 22745., 27624., 65414., 720., 5714., 741., 36880.]) - stable_count_stationary(mid_date)float644.997e+04 4.807e+04 ... 3.666e+04
- description :
- number of valid pixels over stationary or slow-flowing surfaces
- standard_name :
- stable_count_stationary
- units :
- count
array([49966., 48073., 303., 33034., 15317., 29397., 57881., 11745., 37249., 3328., 11144., 38786., 65160., 25475., 47735., 61322., 55699., 50706., 50666., 26524., 11672., 54765., 65361., 30703., 48711., 53048., 59176., 62314., 47070., 48888., 24233., 13263., 22702., 22907., 4018., 20801., 26847., 33581., 17051., 20313., 34898., 24311., 11918., 14255., 854., 63893., 664., 48469., 14334., 22758., 40298., 17217., 19186., 24607., 3325., 45674., 13622., 18203., 57587., 57691., 49837., 43783., 1201., 8257., 55254., 3393., 50063., 23712., 32251., 35705., 48520., 20837., 44025., 2523., 6459., 25714., 16999., 7926., 9028., 53551., 48451., 25075., 54163., 18290., 9795., 57504., 50618., 5699., 47462., 25253., 21756., 7926., 32465., 13509., 57164., 65487., 7084., 42602., 38503., 35417., 54595., 818., 23467., 37409., 29776., 35448., 23144., 64276., 21197., 1207., 8606., 56376., 21813., 56012., 31389., 65294., 52383., 53189., 755., 27655., 58126., 1404., 54542., 23774., 15492., 16333., 55708., 23157., 21400., 56958., 24653., 22206., 50416., 15050., 974., 52083., 34016., 30198., 44341., 53557., 38135., 9866., 6522., 24581., 59787., 6340., 1160., 65195., 39592., 46419., 51581., 29483., 33011., 46589., 50920., 16480., 17286., 62451., 5505., 56517., ... 9004., 21593., 23905., 30383., 16942., 22941., 30534., 20923., 25205., 24625., 44103., 24357., 31437., 53151., 14934., 16799., 12184., 56748., 4249., 19511., 21640., 33733., 11876., 33225., 9185., 16593., 11519., 63314., 6104., 13893., 14533., 57261., 63018., 56920., 38064., 32711., 55129., 7059., 27468., 49458., 65282., 17593., 55130., 15438., 44889., 15777., 32578., 17236., 36879., 20804., 38726., 5770., 30066., 31533., 33904., 35181., 14161., 873., 10199., 24148., 14633., 20193., 45850., 23312., 22448., 51561., 23655., 33411., 30384., 44593., 7192., 45351., 2744., 6638., 65203., 6667., 3872., 2381., 105., 33177., 46110., 53471., 23036., 45115., 27790., 48108., 31610., 13088., 49025., 14576., 15454., 40977., 61909., 55746., 50068., 31038., 37007., 35190., 2323., 28814., 1635., 6825., 41348., 3611., 45925., 6795., 22592., 4678., 34536., 46728., 18440., 9141., 59213., 5137., 8486., 7226., 2542., 45022., 18757., 53618., 2411., 39766., 47998., 43279., 54898., 45476., 29048., 33988., 22693., 21080., 28782., 24120., 35082., 52449., 41838., 18095., 42759., 12144., 7826., 4920., 13393., 15234., 2163., 53008., 8496., 56534., 15672., 62238., 608., 45667., 26900., 22747., 27302., 64980., 65202., 5504., 64491., 36655.]) - stable_shift_flag(mid_date)float641.0 1.0 1.0 1.0 ... 1.0 1.0 1.0 1.0
- description :
- flag for applying velocity bias correction: 0 = no correction; 1 = correction from overlapping stable surface mask (stationary or slow-flowing surfaces with velocity < 15 m/yr)(top priority); 2 = correction from slowest 25% of overlapping velocities (second priority)
- standard_name :
- stable_shift_flag
array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.]) - v(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity magnitude
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_velocity
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - v_error(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity magnitude error
- grid_mapping :
- mapping
- standard_name :
- velocity_error
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - va(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity in radar azimuth direction
- grid_mapping :
- mapping
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - va_error(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- error for velocity in radar azimuth direction
- standard_name :
- va_error
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - va_error_modeled(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- va_error_modeled
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - va_error_slow(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- va_error_slow
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - va_error_stationary(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- va_error_stationary
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - va_stable_shift(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- applied va shift calibrated using pixels over stable or slow surfaces
- standard_name :
- va_stable_shift
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - va_stable_shift_slow(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- va shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- va_stable_shift_slow
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - va_stable_shift_stationary(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- va shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- va_stable_shift_stationary
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vr(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity in radar range direction
- grid_mapping :
- mapping
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - vr_error(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- error for velocity in radar range direction
- standard_name :
- vr_error
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vr_error_modeled(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vr_error_modeled
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vr_error_slow(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vr_error_slow
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vr_error_stationary(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vr_error_stationary
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vr_stable_shift(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- applied vr shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vr_stable_shift
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vr_stable_shift_slow(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- vr shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vr_stable_shift_slow
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vr_stable_shift_stationary(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- vr shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vr_stable_shift_stationary
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vx(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity component in x direction
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_x_velocity
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - vx_error(mid_date)float32321.3 61.7 119.5 ... 5.5 11.3 51.0
- description :
- best estimate of x_velocity error: vx_error is populated according to the approach used for the velocity bias correction as indicated in "stable_shift_flag"
- standard_name :
- vx_error
- units :
- meter/year
array([321.3, 61.7, 119.5, 8.6, 7.1, 1.5, 322.9, 2. , 337.7, 46.7, 7.8, 6.5, 50.6, 8.8, 363.2, 8.1, 2.5, 8. , 120.2, 1.9, 10.7, 99.5, 3. , 10.2, 15. , 107.6, 3.3, 2.5, 8. , 8. , 6.8, 2.3, 377.4, 7.5, 2.3, 5.7, 51.7, 59. , 8.5, 2.5, 2.2, 6.6, 2.5, 1.9, 3.2, 2.2, 7. , 2.3, 7. , 10. , 4. , 2.5, 26.1, 7.4, 7.5, 7.7, 76.3, 10.7, 374.1, 2.2, 6.2, 78.1, 12.8, 3. , 2.6, 1.9, 2.6, 18.1, 53.8, 6.2, 2. , 10. , 6.4, 8.9, 11. , 1.8, 9.9, 12.1, 21.2, 148.5, 2.4, 2.5, 3.1, 7.3, 357.7, 5.4, 7.4, 3.4, 11.9, 37.2, 34.5, 9.5, 365.1, 33.6, 2.2, 39.7, 72.9, 2.3, 8.4, 14.3, 8.4, 10. , 2.3, 10.9, 2.3, 2.9, 16.4, 1.8, 68.9, 7.9, 4. , 11.5, 117.2, 2. , 13.2, 15.4, 1.8, 2. , 8. , 136.6, 42.9, 41.5, 16.1, 8.5, 37. , 2.5, 2.4, 76.6, 1.7, 11.4, 7. , 29.5, 110.7, 2.3, 10.6, 11.4, 2.2, 11.4, 7. , 149.5, 2.4, 8.9, 3.1, 33.2, 2.3, 25.8, 16.1, 7. , 52.1, 4.3, 8.2, 330.7, 24. , 450.8, 18. , 10.1, 41.7, 61.2, 3.7, 10.6, 2.4, 11.6, 2.3, 20.8, 9.1, 110.7, 2.4, 7.5, 2.1, 10.6, 5.9, 34. , 2.2, 4.3, 1.8, 2.4, 2.3, 2.5, 46.4, 7.4, ... 10.4, 4.9, 9.1, 7.2, 31.4, 6.3, 6.3, 19.6, 16.7, 3.9, 3.3, 1.5, 22.2, 1.9, 7.1, 1.9, 9. , 10.4, 15.8, 10. , 4.9, 9.4, 50. , 63.4, 9.5, 2.9, 4.6, 5.1, 6.7, 11. , 5.9, 2.9, 15.2, 272. , 3.6, 13.4, 19.6, 7.6, 14. , 9.6, 6.5, 7.5, 12.5, 40.7, 10. , 29.8, 43.2, 6.4, 71.6, 2.7, 17.8, 9.6, 12.7, 1.6, 19.9, 8. , 10.3, 15.7, 5.1, 10.4, 29.5, 6. , 2.8, 3.9, 14.7, 2.2, 5.2, 2.1, 19.8, 2.7, 19. , 26. , 7. , 10.7, 13.4, 4.4, 23.8, 19.6, 2.4, 10.5, 7.9, 43. , 11.8, 6.2, 33.4, 16.2, 10.3, 7. , 11.4, 3.7, 8.3, 10.2, 4.1, 44.3, 101. , 6.1, 56.2, 4. , 8.4, 7.1, 8.5, 9.8, 2.4, 10.8, 2.4, 4.4, 13.7, 2. , 4.9, 7.3, 16.9, 4.9, 6.6, 31.3, 31. , 152.6, 5.2, 39.9, 5.1, 2.4, 6.4, 14.8, 3. , 11.9, 5.9, 22.1, 4.5, 3.9, 2. , 7.2, 23.2, 11.1, 3.2, 13.2, 9.7, 5.1, 2.2, 8.5, 8.5, 2.4, 13. , 12.7, 162.5, 9.3, 10.7, 3.5, 23.3, 7.6, 7.1, 5.8, 15.9, 5.9, 2.1, 14.5, 2.8, 66.5, 29.7, 5.8, 3.7, 15.4, 7.1, 36. , 1.9, 26.1, 6.9, 6.2, 3.9, 51.1, 3.8, 21.7, 16.2, 35.9, 35.3, 5.5, 11.3, 51. ], dtype=float32) - vx_error_modeled(mid_date)float321.163e+03 232.7 ... 97.0 166.2
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vx_error_modeled
- units :
- meter/year
array([1163.2, 232.7, 387.9, 28.4, 27.1, 20.8, 1163.2, 26.4, 1163.2, 166.2, 24.8, 24.8, 166.2, 28.4, 1163.8, 25.9, 29.1, 27.1, 387.8, 25.3, 33.2, 387.8, 30.6, 116.3, 193.9, 387.9, 34.2, 18.8, 24.8, 25.9, 22. , 27.7, 1163.9, 23.7, 17.6, 22. , 166.2, 232.7, 29.8, 22.4, 23.3, 19.7, 20.8, 21.5, 32.3, 24.2, 22.8, 25.3, 23.7, 31.4, 38.8, 22.4, 89.5, 23.7, 22.8, 27.1, 232.7, 29.8, 1164. , 27.7, 36.4, 232.7, 31.4, 29.1, 29.1, 22.4, 21.5, 145.4, 166.2, 18.5, 17.6, 28.4, 21.2, 33.2, 145.4, 24.2, 97. , 29.8, 68.4, 387.8, 22.4, 26.4, 26.4, 41.6, 1163.9, 17.4, 22. , 32.3, 97. , 129.3, 105.8, 31.4, 1163.3, 581.7, 18.8, 129.3, 232.7, 20.8, 25.9, 193.9, 22.8, 23.7, 18.2, 35.3, 23.3, 21.5, 193.9, 24.2, 232.7, 24.8, 36.4, 64.6, 387.8, 21.5, 116.3, 116.3, 22.4, 25.3, 24.8, 387.9, 581.7, 581.7, 55.4, 97. , 581.7, 30.6, 21.5, 232.7, 23.3, 37.5, 23.7, 105.8, 387.8, 18.2, 145.4, 145.4, 23.3, 116.3, 20.4, 387.8, 29.1, 24.8, 27.7, 105.8, 20.1, 77.6, 193.9, 22.8, 166.2, 25.9, 52.9, 1163.2, 290.9, 1163.2, 145.4, 28.4, 581.7, 166.2, 30.6, 97. , ... 46.5, 22. , 38.8, 31.4, 129.3, 166.2, 27.1, 26.4, 38.8, 18.5, 72.7, 35.3, 17.4, 27.7, 43.1, 1163.2, 34.2, 145.4, 50.6, 20.4, 43.1, 83.1, 19.1, 64.6, 29.8, 89.5, 22.8, 68.4, 105.8, 19.7, 166.2, 17.1, 61.2, 35.3, 116.3, 25.3, 55.4, 64.6, 72.7, 40.1, 17.4, 97. , 61.2, 52.9, 20.1, 38.8, 37.5, 17.1, 17.9, 21.5, 61.2, 19.4, 68.4, 89.5, 64.6, 40.1, 46.5, 41.6, 77.6, 46.5, 29.1, 25.9, 83.1, 105.8, 33.2, 48.5, 68.4, 50.6, 37.5, 20.4, 61.2, 30.6, 29.8, 50.6, 19.7, 166.2, 232.7, 18.5, 129.3, 34.2, 19.1, 17.4, 83.1, 35.3, 19.4, 24.8, 24.2, 41.6, 35.3, 22.4, 44.7, 24.8, 46.5, 17.9, 20.4, 77.6, 77.6, 387.8, 48.5, 89.5, 38.8, 22.4, 64.6, 50.6, 27.7, 31.4, 17.4, 68.4, 41.6, 30.6, 17.6, 48.5, 55.4, 33.2, 32.3, 46.5, 21.2, 38.8, 18.8, 72.7, 83.1, 30.6, 50.6, 37.5, 387.8, 19.7, 40.1, 19.1, 77.6, 31.4, 22.8, 35.3, 46.5, 52.9, 17.1, 55.4, 17.6, 232.7, 68.4, 25.9, 34.2, 37.5, 28.4, 166.2, 17.6, 89.5, 58.2, 21.2, 20.4, 129.3, 22.8, 55.4, 40.1, 105.8, 105.8, 18.5, 97. , 166.2], dtype=float32) - vx_error_slow(mid_date)float32321.0 61.6 119.3 ... 5.5 11.2 50.9
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vx_error_slow
- units :
- meter/year
array([321. , 61.6, 119.3, 8.5, 7.1, 1.5, 322.2, 2. , 337.5, 46.6, 7.8, 6.5, 50.5, 8.8, 363. , 8.1, 2.5, 8. , 120. , 1.9, 10.7, 99.4, 3. , 10.2, 15. , 107.5, 3.3, 2.5, 8. , 8. , 6.8, 2.3, 376.7, 7.5, 2.3, 5.7, 51.6, 58.9, 8.5, 2.5, 2.2, 6.6, 2.5, 1.9, 3.2, 2.2, 7. , 2.3, 7. , 10. , 4. , 2.5, 26.1, 7.4, 7.5, 7.7, 76.1, 10.7, 373.2, 2.2, 6.2, 78. , 12.8, 3. , 2.6, 1.9, 2.6, 18.1, 53.7, 6.2, 2. , 10. , 6.4, 8.9, 11. , 1.8, 9.9, 12.1, 21.2, 148.4, 2.4, 2.5, 3.1, 7.3, 357.3, 5.4, 7.4, 3.4, 11.9, 37.2, 34.5, 9.5, 364.7, 33.6, 2.2, 39.6, 72.8, 2.3, 8.4, 14.2, 8.4, 10. , 2.3, 10.9, 2.3, 2.9, 16.4, 1.8, 68.7, 7.9, 4. , 11.5, 117.1, 2. , 13.1, 15.4, 1.8, 2. , 8. , 136.4, 42.9, 41.5, 16.1, 8.5, 37. , 2.5, 2.5, 76.5, 1.7, 11.4, 7. , 29.4, 110.5, 2.3, 10.6, 11.4, 2.2, 11.4, 7. , 149.1, 2.4, 8.8, 3.1, 33.1, 2.3, 25.8, 16.1, 7. , 52.1, 4.3, 8.2, 329.9, 24. , 449.9, 18. , 10.1, 41.7, 61.1, 3.7, 10.6, 2.4, 11.6, 2.3, 20.8, 9.1, 110.5, 2.4, 7.5, 2.1, 10.6, 5.9, 34. , 2.2, 4.3, 1.8, 2.4, 2.3, 2.5, 46.4, 7.4, ... 10.4, 4.9, 9.1, 7.2, 31.4, 6.3, 6.3, 19.6, 16.6, 3.9, 3.3, 1.5, 22.2, 1.9, 7.1, 1.9, 9. , 10.4, 15.8, 10. , 4.9, 9.4, 49.9, 63.3, 9.5, 2.9, 4.6, 5.1, 6.7, 11. , 5.8, 2.9, 15.2, 271.7, 3.6, 13.4, 19.6, 7.6, 14. , 9.6, 6.5, 7.5, 12.5, 40.7, 10. , 29.8, 43.2, 6.4, 71.6, 2.7, 17.8, 9.6, 12.7, 1.6, 19.9, 8. , 10.3, 15.6, 5.1, 10.4, 29.5, 6. , 2.8, 3.9, 14.6, 2.2, 5.2, 2.1, 19.8, 2.7, 19. , 26. , 7. , 10.7, 13.4, 4.4, 23.8, 19.6, 2.4, 10.5, 7.9, 43. , 11.8, 6.2, 33.4, 16.2, 10.3, 7. , 11.4, 3.7, 8.3, 10.1, 4.1, 44.3, 100.6, 6.1, 56.2, 3.9, 8.4, 7.1, 8.5, 9.8, 2.4, 10.8, 2.4, 4.4, 13.7, 2. , 4.9, 7.3, 16.9, 4.9, 6.6, 31.4, 31. , 151.7, 5.2, 39.9, 5.1, 2.4, 6.4, 14.8, 3. , 11.9, 5.9, 22.1, 4.5, 3.9, 2. , 7.2, 23.2, 11.1, 3.2, 13.2, 9.7, 5.1, 2.2, 8.5, 8.5, 2.4, 13.1, 12.7, 162.4, 9.3, 10.6, 3.5, 23.3, 7.6, 7.1, 5.8, 15.8, 5.9, 2.1, 14.4, 2.8, 66.5, 29.6, 5.7, 3.7, 15.3, 7.1, 35.9, 1.9, 26.1, 6.9, 6.2, 3.9, 51.2, 3.8, 21.7, 16.3, 36.4, 35.2, 5.5, 11.2, 50.9], dtype=float32) - vx_error_stationary(mid_date)float32321.3 61.7 119.5 ... 5.5 11.3 51.0
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 meter/year identified from an external mask
- standard_name :
- vx_error_stationary
- units :
- meter/year
array([321.3, 61.7, 119.5, 8.6, 7.1, 1.5, 322.9, 2. , 337.7, 46.7, 7.8, 6.5, 50.6, 8.8, 363.2, 8.1, 2.5, 8. , 120.2, 1.9, 10.7, 99.5, 3. , 10.2, 15. , 107.6, 3.3, 2.5, 8. , 8. , 6.8, 2.3, 377.4, 7.5, 2.3, 5.7, 51.7, 59. , 8.5, 2.5, 2.2, 6.6, 2.5, 1.9, 3.2, 2.2, 7. , 2.3, 7. , 10. , 4. , 2.5, 26.1, 7.4, 7.5, 7.7, 76.3, 10.7, 374.1, 2.2, 6.2, 78.1, 12.8, 3. , 2.6, 1.9, 2.6, 18.1, 53.8, 6.2, 2. , 10. , 6.4, 8.9, 11. , 1.8, 9.9, 12.1, 21.2, 148.5, 2.4, 2.5, 3.1, 7.3, 357.7, 5.4, 7.4, 3.4, 11.9, 37.2, 34.5, 9.5, 365.1, 33.6, 2.2, 39.7, 72.9, 2.3, 8.4, 14.3, 8.4, 10. , 2.3, 10.9, 2.3, 2.9, 16.4, 1.8, 68.9, 7.9, 4. , 11.5, 117.2, 2. , 13.2, 15.4, 1.8, 2. , 8. , 136.6, 42.9, 41.5, 16.1, 8.5, 37. , 2.5, 2.4, 76.6, 1.7, 11.4, 7. , 29.5, 110.7, 2.3, 10.6, 11.4, 2.2, 11.4, 7. , 149.5, 2.4, 8.9, 3.1, 33.2, 2.3, 25.8, 16.1, 7. , 52.1, 4.3, 8.2, 330.7, 24. , 450.8, 18. , 10.1, 41.7, 61.2, 3.7, 10.6, 2.4, 11.6, 2.3, 20.8, 9.1, 110.7, 2.4, 7.5, 2.1, 10.6, 5.9, 34. , 2.2, 4.3, 1.8, 2.4, 2.3, 2.5, 46.4, 7.4, ... 10.4, 4.9, 9.1, 7.2, 31.4, 6.3, 6.3, 19.6, 16.7, 3.9, 3.3, 1.5, 22.2, 1.9, 7.1, 1.9, 9. , 10.4, 15.8, 10. , 4.9, 9.4, 50. , 63.4, 9.5, 2.9, 4.6, 5.1, 6.7, 11. , 5.9, 2.9, 15.2, 272. , 3.6, 13.4, 19.6, 7.6, 14. , 9.6, 6.5, 7.5, 12.5, 40.7, 10. , 29.8, 43.2, 6.4, 71.6, 2.7, 17.8, 9.6, 12.7, 1.6, 19.9, 8. , 10.3, 15.7, 5.1, 10.4, 29.5, 6. , 2.8, 3.9, 14.7, 2.2, 5.2, 2.1, 19.8, 2.7, 19. , 26. , 7. , 10.7, 13.4, 4.4, 23.8, 19.6, 2.4, 10.5, 7.9, 43. , 11.8, 6.2, 33.4, 16.2, 10.3, 7. , 11.4, 3.7, 8.3, 10.2, 4.1, 44.3, 101. , 6.1, 56.2, 4. , 8.4, 7.1, 8.5, 9.8, 2.4, 10.8, 2.4, 4.4, 13.7, 2. , 4.9, 7.3, 16.9, 4.9, 6.6, 31.3, 31. , 152.6, 5.2, 39.9, 5.1, 2.4, 6.4, 14.8, 3. , 11.9, 5.9, 22.1, 4.5, 3.9, 2. , 7.2, 23.2, 11.1, 3.2, 13.2, 9.7, 5.1, 2.2, 8.5, 8.5, 2.4, 13. , 12.7, 162.5, 9.3, 10.7, 3.5, 23.3, 7.6, 7.1, 5.8, 15.9, 5.9, 2.1, 14.5, 2.8, 66.5, 29.7, 5.8, 3.7, 15.4, 7.1, 36. , 1.9, 26.1, 6.9, 6.2, 3.9, 51.1, 3.8, 21.7, 16.2, 35.9, 35.3, 5.5, 11.3, 51. ], dtype=float32) - vx_stable_shift(mid_date)float32-42.8 8.6 0.0 -2.1 ... 0.3 3.6 30.8
- description :
- applied vx shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vx_stable_shift
- units :
- meter/year
array([-4.280e+01, 8.600e+00, 0.000e+00, -2.100e+00, 1.000e+00, 8.000e-01, -8.550e+01, 0.000e+00, 0.000e+00, -1.220e+01, 2.100e+00, 9.000e-01, 1.220e+01, -7.000e-01, -4.280e+01, 0.000e+00, 0.000e+00, -2.200e+00, 3.970e+01, 0.000e+00, 0.000e+00, 2.640e+01, 0.000e+00, 0.000e+00, 0.000e+00, 1.430e+01, 0.000e+00, 0.000e+00, 0.000e+00, 1.300e+00, -1.400e+00, -6.000e-01, -4.280e+01, 1.500e+00, 0.000e+00, 6.000e-01, 1.830e+01, 8.600e+00, -1.100e+00, -8.000e-01, 0.000e+00, 1.400e+00, 0.000e+00, 8.000e-01, -1.200e+00, 0.000e+00, -8.000e-01, 0.000e+00, -9.000e-01, -8.000e-01, 1.400e+00, -8.000e-01, 5.300e+00, 1.700e+00, -2.000e-01, -4.000e-01, 1.220e+01, 9.000e-01, 4.900e+00, 2.000e-01, 1.300e+00, 7.300e+00, -4.000e+00, 0.000e+00, 1.100e+00, 8.000e-01, -1.300e+00, -5.300e+00, -2.000e-01, 0.000e+00, 0.000e+00, 5.000e-01, 1.300e+00, 2.900e+00, 0.000e+00, 0.000e+00, 0.000e+00, -4.300e+00, -1.200e+00, -4.930e+01, 0.000e+00, 0.000e+00, 6.000e-01, 1.500e+00, 0.000e+00, -5.000e-01, -8.000e-01, 2.100e+00, -3.600e+00, 1.170e+01, 0.000e+00, 3.500e+00, 4.280e+01, 0.000e+00, 0.000e+00, -9.500e+00, 8.600e+00, 0.000e+00, 4.000e-01, 7.100e+00, ... 1.200e+00, -3.100e+00, 7.700e+00, -1.000e-01, -8.000e-01, 1.680e+01, 6.000e-01, 9.600e+00, 8.000e-01, -5.300e+00, -1.100e+00, 4.400e+00, -3.400e+00, -1.600e+00, 2.450e+01, 9.200e+00, 1.000e+00, 1.430e+01, 1.300e+00, 8.000e-01, 3.800e+00, -2.000e-01, 2.600e+00, 0.000e+00, 5.300e+00, 9.000e-01, 1.500e+00, 6.500e+00, 0.000e+00, 2.600e+00, 0.000e+00, 7.600e+00, 1.400e+00, 1.100e+00, 1.700e+00, 3.200e+00, 9.600e+00, 0.000e+00, 1.610e+01, -1.400e+00, 1.300e+00, -1.300e+00, 9.200e+00, 0.000e+00, -8.100e+00, 4.100e+00, 1.200e+01, 0.000e+00, 1.900e+00, -4.000e-01, -1.000e-01, 1.400e+01, 2.100e+00, 1.200e+00, 2.000e-01, 3.100e+00, -1.400e+00, 0.000e+00, 2.700e+00, 8.000e-01, 1.000e+00, 9.800e+00, 8.300e+00, 2.850e+01, 7.000e-01, 5.000e+00, -3.000e-01, 6.500e+00, 8.100e+00, 1.400e+00, -1.200e+00, 6.200e+00, -1.900e+00, 6.000e-01, 1.020e+01, 7.000e-01, 8.190e+01, 7.200e+00, 0.000e+00, -1.200e+00, 5.300e+00, -7.000e-01, 3.400e+00, 2.000e-01, -1.800e+00, 1.800e+00, 0.000e+00, -1.200e+00, 6.010e+01, -1.500e+00, 1.590e+01, 1.550e+01, 5.940e+01, -6.300e+00, 3.000e-01, 3.600e+00, 3.080e+01], dtype=float32) - vx_stable_shift_slow(mid_date)float32-42.8 8.6 0.0 -2.1 ... 0.3 3.6 30.5
- description :
- vx shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vx_stable_shift_slow
- units :
- meter/year
array([-4.280e+01, 8.600e+00, 0.000e+00, -2.100e+00, 1.000e+00, 8.000e-01, -8.550e+01, 0.000e+00, 0.000e+00, -1.220e+01, 2.100e+00, 9.000e-01, 1.220e+01, -7.000e-01, -4.280e+01, 0.000e+00, 0.000e+00, -2.200e+00, 4.030e+01, 0.000e+00, 0.000e+00, 2.700e+01, 0.000e+00, 0.000e+00, 0.000e+00, 1.430e+01, 0.000e+00, 0.000e+00, 0.000e+00, 1.300e+00, -1.400e+00, -7.000e-01, -4.280e+01, 1.500e+00, 0.000e+00, 6.000e-01, 1.830e+01, 8.600e+00, -1.100e+00, -8.000e-01, 0.000e+00, 1.400e+00, 0.000e+00, 8.000e-01, -1.200e+00, 0.000e+00, -8.000e-01, 0.000e+00, -9.000e-01, -7.000e-01, 1.400e+00, -8.000e-01, 5.300e+00, 1.700e+00, -1.000e-01, -4.000e-01, 1.230e+01, 9.000e-01, 6.400e+00, 2.000e-01, 1.300e+00, 7.500e+00, -4.000e+00, 0.000e+00, 1.100e+00, 8.000e-01, -1.300e+00, -5.300e+00, -1.000e-01, 0.000e+00, 0.000e+00, 5.000e-01, 1.300e+00, 2.900e+00, 0.000e+00, 0.000e+00, 0.000e+00, -4.200e+00, -1.200e+00, -4.900e+01, 0.000e+00, 0.000e+00, 6.000e-01, 1.500e+00, 0.000e+00, -5.000e-01, -8.000e-01, 2.100e+00, -3.600e+00, 1.190e+01, 0.000e+00, 3.500e+00, 4.280e+01, 0.000e+00, 0.000e+00, -9.500e+00, 8.600e+00, 0.000e+00, 5.000e-01, 7.100e+00, ... 1.200e+00, -3.100e+00, 7.300e+00, -2.000e-01, -8.000e-01, 1.680e+01, 6.000e-01, 9.700e+00, 8.000e-01, -5.300e+00, -1.100e+00, 4.400e+00, -3.300e+00, -1.600e+00, 2.440e+01, 8.600e+00, 1.000e+00, 1.400e+01, 1.300e+00, 7.000e-01, 3.800e+00, -1.000e-01, 2.600e+00, 0.000e+00, 5.300e+00, 9.000e-01, 1.500e+00, 6.500e+00, 0.000e+00, 2.500e+00, 0.000e+00, 7.600e+00, 1.400e+00, 1.100e+00, 1.700e+00, 3.100e+00, 1.020e+01, 0.000e+00, 1.580e+01, -1.400e+00, 1.300e+00, -1.400e+00, 9.200e+00, 0.000e+00, -8.100e+00, 4.000e+00, 1.200e+01, 0.000e+00, 1.900e+00, -4.000e-01, 0.000e+00, 1.410e+01, 2.100e+00, 1.200e+00, 1.000e-01, 3.100e+00, -1.400e+00, 0.000e+00, 2.700e+00, 7.000e-01, 9.000e-01, 9.800e+00, 8.300e+00, 2.850e+01, 7.000e-01, 5.100e+00, -3.000e-01, 6.400e+00, 8.100e+00, 1.400e+00, -1.200e+00, 6.100e+00, -1.900e+00, 6.000e-01, 1.020e+01, 7.000e-01, 8.180e+01, 7.000e+00, 0.000e+00, -1.200e+00, 5.100e+00, -7.000e-01, 3.500e+00, 3.000e-01, -1.800e+00, 1.900e+00, 0.000e+00, -1.200e+00, 6.000e+01, -1.500e+00, 1.590e+01, 1.540e+01, 5.920e+01, -6.300e+00, 3.000e-01, 3.600e+00, 3.050e+01], dtype=float32) - vx_stable_shift_stationary(mid_date)float32-42.8 8.6 0.0 -2.1 ... 0.3 3.6 30.8
- description :
- vx shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vx_stable_shift_stationary
- units :
- meter/year
array([-4.280e+01, 8.600e+00, 0.000e+00, -2.100e+00, 1.000e+00, 8.000e-01, -8.550e+01, 0.000e+00, 0.000e+00, -1.220e+01, 2.100e+00, 9.000e-01, 1.220e+01, -7.000e-01, -4.280e+01, 0.000e+00, 0.000e+00, -2.200e+00, 3.970e+01, 0.000e+00, 0.000e+00, 2.640e+01, 0.000e+00, 0.000e+00, 0.000e+00, 1.430e+01, 0.000e+00, 0.000e+00, 0.000e+00, 1.300e+00, -1.400e+00, -6.000e-01, -4.280e+01, 1.500e+00, 0.000e+00, 6.000e-01, 1.830e+01, 8.600e+00, -1.100e+00, -8.000e-01, 0.000e+00, 1.400e+00, 0.000e+00, 8.000e-01, -1.200e+00, 0.000e+00, -8.000e-01, 0.000e+00, -9.000e-01, -8.000e-01, 1.400e+00, -8.000e-01, 5.300e+00, 1.700e+00, -2.000e-01, -4.000e-01, 1.220e+01, 9.000e-01, 4.900e+00, 2.000e-01, 1.300e+00, 7.300e+00, -4.000e+00, 0.000e+00, 1.100e+00, 8.000e-01, -1.300e+00, -5.300e+00, -2.000e-01, 0.000e+00, 0.000e+00, 5.000e-01, 1.300e+00, 2.900e+00, 0.000e+00, 0.000e+00, 0.000e+00, -4.300e+00, -1.200e+00, -4.930e+01, 0.000e+00, 0.000e+00, 6.000e-01, 1.500e+00, 0.000e+00, -5.000e-01, -8.000e-01, 2.100e+00, -3.600e+00, 1.170e+01, 0.000e+00, 3.500e+00, 4.280e+01, 0.000e+00, 0.000e+00, -9.500e+00, 8.600e+00, 0.000e+00, 4.000e-01, 7.100e+00, ... 1.200e+00, -3.100e+00, 7.700e+00, -1.000e-01, -8.000e-01, 1.680e+01, 6.000e-01, 9.600e+00, 8.000e-01, -5.300e+00, -1.100e+00, 4.400e+00, -3.400e+00, -1.600e+00, 2.450e+01, 9.200e+00, 1.000e+00, 1.430e+01, 1.300e+00, 8.000e-01, 3.800e+00, -2.000e-01, 2.600e+00, 0.000e+00, 5.300e+00, 9.000e-01, 1.500e+00, 6.500e+00, 0.000e+00, 2.600e+00, 0.000e+00, 7.600e+00, 1.400e+00, 1.100e+00, 1.700e+00, 3.200e+00, 9.600e+00, 0.000e+00, 1.610e+01, -1.400e+00, 1.300e+00, -1.300e+00, 9.200e+00, 0.000e+00, -8.100e+00, 4.100e+00, 1.200e+01, 0.000e+00, 1.900e+00, -4.000e-01, -1.000e-01, 1.400e+01, 2.100e+00, 1.200e+00, 2.000e-01, 3.100e+00, -1.400e+00, 0.000e+00, 2.700e+00, 8.000e-01, 1.000e+00, 9.800e+00, 8.300e+00, 2.850e+01, 7.000e-01, 5.000e+00, -3.000e-01, 6.500e+00, 8.100e+00, 1.400e+00, -1.200e+00, 6.200e+00, -1.900e+00, 6.000e-01, 1.020e+01, 7.000e-01, 8.190e+01, 7.200e+00, 0.000e+00, -1.200e+00, 5.300e+00, -7.000e-01, 3.400e+00, 2.000e-01, -1.800e+00, 1.800e+00, 0.000e+00, -1.200e+00, 6.010e+01, -1.500e+00, 1.590e+01, 1.550e+01, 5.940e+01, -6.300e+00, 3.000e-01, 3.600e+00, 3.080e+01], dtype=float32) - vy(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity component in y direction
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_y_velocity
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - vy_error(mid_date)float32112.5 37.6 54.2 ... 8.9 11.3 25.4
- description :
- best estimate of y_velocity error: vy_error is populated according to the approach used for the velocity bias correction as indicated in "stable_shift_flag"
- standard_name :
- vy_error
- units :
- meter/year
array([112.5, 37.6, 54.2, 5.9, 6. , 2.2, 150.3, 3.4, 134.7, 27.4, 4.2, 5.7, 27.9, 5.4, 410.3, 4.6, 4.6, 5.4, 72.9, 3.5, 6.6, 56. , 6. , 15.8, 22.5, 64.8, 5.1, 4.5, 3.5, 5.2, 4.3, 4.3, 145.8, 4.5, 4.3, 5. , 29.5, 39.5, 8.6, 3.5, 2.9, 3.3, 3.6, 2.6, 5.1, 3.4, 4. , 3.6, 7.4, 6.5, 6.3, 3.6, 14.3, 5.1, 4.2, 8.1, 36. , 5.6, 209. , 2.7, 10.6, 37. , 5.5, 5.5, 3.9, 2.5, 3.7, 28. , 33.9, 3.5, 4. , 5.3, 4.5, 7.9, 16.2, 2.5, 15.6, 5.2, 12.4, 58.8, 4.5, 4.6, 6.3, 13.7, 180. , 4.6, 4.5, 5.9, 19.5, 27.7, 22.5, 6.1, 157.8, 37.3, 4. , 21.6, 33.8, 4.5, 3.8, 18.3, 4.4, 3.8, 3. , 7.6, 3.5, 5.4, 25.8, 2.3, 29.3, 4.2, 6.1, 20.1, 53. , 3. , 20.2, 23.2, 2.6, 3. , 3. , 57.5, 51.9, 57.1, 12.2, 12.5, 48. , 3.6, 4.3, 32.4, 2.5, 11.6, 5.4, 24. , 58.1, 4. , 13.6, 16.1, 4.6, 19.2, 4.2, 48.9, 3.6, 4.6, 6.1, 18.5, 4.3, 14. , 27.6, 4.4, 26.8, 6.9, 16.5, 146.6, 33.6, 166.6, 26.8, 4.1, 63.7, 27.2, 5.2, 16.8, 3.3, 20.5, 3. , 10.9, 3.4, 58.9, 3.9, 4.2, 3.6, 3.3, 4.8, 21.5, 3.5, 5.9, 3.2, 3. , 3.6, 2.9, 25.1, 3.7, ... 5.9, 5.8, 4. , 3.7, 36.8, 11.1, 11.1, 19.4, 15.8, 6.6, 4.7, 1.7, 9.8, 2.9, 5.2, 3.3, 6.2, 5.6, 10.4, 5.6, 5.8, 6.6, 23.8, 24.8, 4.5, 4.3, 6.7, 6.5, 10. , 10.4, 5. , 3.2, 9.3, 161.1, 4.2, 16.6, 6.6, 4. , 13.8, 12.6, 3.9, 12.2, 5.3, 16.6, 5.9, 17.4, 18.7, 3.7, 31.2, 3.9, 16.4, 8.3, 16.8, 1.3, 17.6, 12. , 22.9, 7.7, 3.6, 17.5, 14.4, 8.5, 3.3, 5.4, 8.6, 2.5, 3.3, 2.9, 11.1, 4.7, 12.2, 21.6, 8.2, 7.6, 11.1, 7.2, 13.7, 7.2, 2.4, 3.5, 11.2, 28.6, 9. , 5.4, 14. , 8.7, 6.3, 5. , 22.6, 3.6, 3.5, 22.2, 5.7, 33.4, 61.6, 4.8, 31.9, 6.4, 5.7, 3.8, 14.8, 7.1, 3.7, 3.7, 2.9, 6.3, 5.7, 2.8, 6. , 3.3, 11.7, 3.9, 4.5, 18.3, 20.9, 62.2, 8.2, 23. , 7.4, 3.1, 10. , 9.7, 3.3, 12.5, 3.8, 17.1, 6.7, 5.4, 4.4, 13.7, 16.9, 7.1, 3.5, 15.8, 5.9, 6.2, 3.2, 12. , 12.7, 2.8, 9.8, 6. , 98.9, 5.5, 14.3, 6.5, 18.8, 3.5, 4.2, 13.9, 8.2, 8.4, 2.6, 10.1, 3.2, 33.7, 17.2, 3.9, 6.8, 11.2, 5.2, 19.3, 2.3, 22.2, 6.9, 8.3, 4.9, 19.2, 7.6, 11.9, 10.8, 17.6, 20.5, 8.9, 11.3, 25.4], dtype=float32) - vy_error_modeled(mid_date)float321.163e+03 232.7 ... 97.0 166.2
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vy_error_modeled
- units :
- meter/year
array([1163.2, 232.7, 387.9, 28.4, 27.1, 20.8, 1163.2, 26.4, 1163.2, 166.2, 24.8, 24.8, 166.2, 28.4, 1163.8, 25.9, 29.1, 27.1, 387.8, 25.3, 33.2, 387.8, 30.6, 116.3, 193.9, 387.9, 34.2, 18.8, 24.8, 25.9, 22. , 27.7, 1163.9, 23.7, 17.6, 22. , 166.2, 232.7, 29.8, 22.4, 23.3, 19.7, 20.8, 21.5, 32.3, 24.2, 22.8, 25.3, 23.7, 31.4, 38.8, 22.4, 89.5, 23.7, 22.8, 27.1, 232.7, 29.8, 1164. , 27.7, 36.4, 232.7, 31.4, 29.1, 29.1, 22.4, 21.5, 145.4, 166.2, 18.5, 17.6, 28.4, 21.2, 33.2, 145.4, 24.2, 97. , 29.8, 68.4, 387.8, 22.4, 26.4, 26.4, 41.6, 1163.9, 17.4, 22. , 32.3, 97. , 129.3, 105.8, 31.4, 1163.3, 581.7, 18.8, 129.3, 232.7, 20.8, 25.9, 193.9, 22.8, 23.7, 18.2, 35.3, 23.3, 21.5, 193.9, 24.2, 232.7, 24.8, 36.4, 64.6, 387.8, 21.5, 116.3, 116.3, 22.4, 25.3, 24.8, 387.9, 581.7, 581.7, 55.4, 97. , 581.7, 30.6, 21.5, 232.7, 23.3, 37.5, 23.7, 105.8, 387.8, 18.2, 145.4, 145.4, 23.3, 116.3, 20.4, 387.8, 29.1, 24.8, 27.7, 105.8, 20.1, 77.6, 193.9, 22.8, 166.2, 25.9, 52.9, 1163.2, 290.9, 1163.2, 145.4, 28.4, 581.7, 166.2, 30.6, 97. , ... 46.5, 22. , 38.8, 31.4, 129.3, 166.2, 27.1, 26.4, 38.8, 18.5, 72.7, 35.3, 17.4, 27.7, 43.1, 1163.2, 34.2, 145.4, 50.6, 20.4, 43.1, 83.1, 19.1, 64.6, 29.8, 89.5, 22.8, 68.4, 105.8, 19.7, 166.2, 17.1, 61.2, 35.3, 116.3, 25.3, 55.4, 64.6, 72.7, 40.1, 17.4, 97. , 61.2, 52.9, 20.1, 38.8, 37.5, 17.1, 17.9, 21.5, 61.2, 19.4, 68.4, 89.5, 64.6, 40.1, 46.5, 41.6, 77.6, 46.5, 29.1, 25.9, 83.1, 105.8, 33.2, 48.5, 68.4, 50.6, 37.5, 20.4, 61.2, 30.6, 29.8, 50.6, 19.7, 166.2, 232.7, 18.5, 129.3, 34.2, 19.1, 17.4, 83.1, 35.3, 19.4, 24.8, 24.2, 41.6, 35.3, 22.4, 44.7, 24.8, 46.5, 17.9, 20.4, 77.6, 77.6, 387.8, 48.5, 89.5, 38.8, 22.4, 64.6, 50.6, 27.7, 31.4, 17.4, 68.4, 41.6, 30.6, 17.6, 48.5, 55.4, 33.2, 32.3, 46.5, 21.2, 38.8, 18.8, 72.7, 83.1, 30.6, 50.6, 37.5, 387.8, 19.7, 40.1, 19.1, 77.6, 31.4, 22.8, 35.3, 46.5, 52.9, 17.1, 55.4, 17.6, 232.7, 68.4, 25.9, 34.2, 37.5, 28.4, 166.2, 17.6, 89.5, 58.2, 21.2, 20.4, 129.3, 22.8, 55.4, 40.1, 105.8, 105.8, 18.5, 97. , 166.2], dtype=float32) - vy_error_slow(mid_date)float32112.5 37.6 54.1 ... 8.9 11.3 25.4
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vy_error_slow
- units :
- meter/year
array([112.5, 37.6, 54.1, 5.9, 6. , 2.2, 150.3, 3.4, 134.7, 27.4, 4.2, 5.7, 27.9, 5.4, 409.5, 4.6, 4.6, 5.4, 72.8, 3.5, 6.6, 55.9, 6. , 15.8, 22.5, 64.7, 5.1, 4.5, 3.5, 5.2, 4.3, 4.3, 145.6, 4.5, 4.3, 5. , 29.4, 39.5, 8.6, 3.5, 2.9, 3.3, 3.6, 2.6, 5.1, 3.4, 4. , 3.6, 7.3, 6.5, 6.3, 3.6, 14.3, 5.1, 4.2, 8. , 36. , 5.6, 208.7, 2.7, 10.6, 36.9, 5.5, 5.5, 3.9, 2.5, 3.7, 28. , 33.9, 3.5, 4. , 5.3, 4.5, 7.9, 16.1, 2.4, 15.6, 5.2, 12.4, 58.7, 4.5, 4.6, 6.3, 13.7, 179.9, 4.6, 4.5, 5.9, 19.5, 27.7, 22.4, 6.1, 157.9, 37.4, 4. , 21.6, 33.8, 4.5, 3.8, 18.3, 4.4, 3.8, 3. , 7.6, 3.5, 5.4, 25.7, 2.3, 29.3, 4.2, 6.1, 20.1, 53. , 3. , 20.2, 23.2, 2.6, 3. , 3. , 57.5, 51.9, 57. , 12.2, 12.5, 48. , 3.6, 4.3, 32.4, 2.5, 11.6, 5.4, 24. , 58.1, 4. , 13.6, 16.1, 4.6, 19.2, 4.2, 48.9, 3.6, 4.6, 6.1, 18.5, 4.3, 14. , 27.6, 4.4, 26.8, 6.9, 16.5, 146.6, 33.6, 166.7, 26.8, 4.1, 63.6, 27.2, 5.2, 16.8, 3.3, 20.5, 3. , 10.9, 3.4, 58.8, 3.9, 4.2, 3.6, 3.3, 4.8, 21.5, 3.5, 5.9, 3.2, 3. , 3.6, 2.9, 25.1, 3.7, ... 5.9, 5.8, 4. , 3.7, 36.8, 11. , 11.2, 19.4, 15.8, 6.6, 4.7, 1.7, 9.8, 2.9, 5.2, 3.3, 6.2, 5.6, 10.4, 5.6, 5.8, 6.6, 23.8, 24.8, 4.5, 4.3, 6.7, 6.5, 10. , 10.4, 5. , 3.2, 9.3, 160.8, 4.2, 16.6, 6.6, 4. , 13.8, 12.6, 3.9, 12.2, 5.3, 16.6, 5.9, 17.5, 18.7, 3.7, 31.2, 3.9, 16.4, 8.3, 16.8, 1.3, 17.6, 12. , 22.9, 7.7, 3.6, 17.5, 14.4, 8.5, 3.3, 5.4, 8.6, 2.5, 3.3, 2.9, 11. , 4.7, 12.2, 21.6, 8.2, 7.6, 11.1, 7.2, 13.8, 7.2, 2.4, 3.5, 11.2, 28.6, 9. , 5.4, 14. , 8.7, 6.3, 5. , 22.6, 3.6, 3.5, 22.2, 5.7, 33.4, 61.5, 4.8, 31.9, 6.4, 5.7, 3.8, 14.8, 7.1, 3.7, 3.7, 2.9, 6.3, 5.7, 2.8, 6. , 3.3, 11.7, 3.9, 4.5, 18.3, 20.9, 62. , 8.1, 23.1, 7.4, 3.1, 10. , 9.7, 3.3, 12.5, 3.8, 17.1, 6.7, 5.4, 4.4, 13.7, 16.9, 7.1, 3.5, 15.8, 5.9, 6.2, 3.2, 12. , 12.7, 2.8, 9.8, 6. , 98.9, 5.5, 14.3, 6.5, 18.8, 3.5, 4.2, 13.9, 8.2, 8.4, 2.6, 10.1, 3.2, 33.7, 17.2, 3.9, 6.8, 11.2, 5.1, 19.3, 2.3, 22.2, 6.9, 8.2, 4.9, 19.2, 7.6, 11.9, 10.9, 17.6, 20.4, 8.9, 11.3, 25.4], dtype=float32) - vy_error_stationary(mid_date)float32112.5 37.6 54.2 ... 8.9 11.3 25.4
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 meter/year identified from an external mask
- standard_name :
- vy_error_stationary
- units :
- meter/year
array([112.5, 37.6, 54.2, 5.9, 6. , 2.2, 150.3, 3.4, 134.7, 27.4, 4.2, 5.7, 27.9, 5.4, 410.3, 4.6, 4.6, 5.4, 72.9, 3.5, 6.6, 56. , 6. , 15.8, 22.5, 64.8, 5.1, 4.5, 3.5, 5.2, 4.3, 4.3, 145.8, 4.5, 4.3, 5. , 29.5, 39.5, 8.6, 3.5, 2.9, 3.3, 3.6, 2.6, 5.1, 3.4, 4. , 3.6, 7.4, 6.5, 6.3, 3.6, 14.3, 5.1, 4.2, 8.1, 36. , 5.6, 209. , 2.7, 10.6, 37. , 5.5, 5.5, 3.9, 2.5, 3.7, 28. , 33.9, 3.5, 4. , 5.3, 4.5, 7.9, 16.2, 2.5, 15.6, 5.2, 12.4, 58.8, 4.5, 4.6, 6.3, 13.7, 180. , 4.6, 4.5, 5.9, 19.5, 27.7, 22.5, 6.1, 157.8, 37.3, 4. , 21.6, 33.8, 4.5, 3.8, 18.3, 4.4, 3.8, 3. , 7.6, 3.5, 5.4, 25.8, 2.3, 29.3, 4.2, 6.1, 20.1, 53. , 3. , 20.2, 23.2, 2.6, 3. , 3. , 57.5, 51.9, 57.1, 12.2, 12.5, 48. , 3.6, 4.3, 32.4, 2.5, 11.6, 5.4, 24. , 58.1, 4. , 13.6, 16.1, 4.6, 19.2, 4.2, 48.9, 3.6, 4.6, 6.1, 18.5, 4.3, 14. , 27.6, 4.4, 26.8, 6.9, 16.5, 146.6, 33.6, 166.6, 26.8, 4.1, 63.7, 27.2, 5.2, 16.8, 3.3, 20.5, 3. , 10.9, 3.4, 58.9, 3.9, 4.2, 3.6, 3.3, 4.8, 21.5, 3.5, 5.9, 3.2, 3. , 3.6, 2.9, 25.1, 3.7, ... 5.9, 5.8, 4. , 3.7, 36.8, 11.1, 11.1, 19.4, 15.8, 6.6, 4.7, 1.7, 9.8, 2.9, 5.2, 3.3, 6.2, 5.6, 10.4, 5.6, 5.8, 6.6, 23.8, 24.8, 4.5, 4.3, 6.7, 6.5, 10. , 10.4, 5. , 3.2, 9.3, 161.1, 4.2, 16.6, 6.6, 4. , 13.8, 12.6, 3.9, 12.2, 5.3, 16.6, 5.9, 17.4, 18.7, 3.7, 31.2, 3.9, 16.4, 8.3, 16.8, 1.3, 17.6, 12. , 22.9, 7.7, 3.6, 17.5, 14.4, 8.5, 3.3, 5.4, 8.6, 2.5, 3.3, 2.9, 11.1, 4.7, 12.2, 21.6, 8.2, 7.6, 11.1, 7.2, 13.7, 7.2, 2.4, 3.5, 11.2, 28.6, 9. , 5.4, 14. , 8.7, 6.3, 5. , 22.6, 3.6, 3.5, 22.2, 5.7, 33.4, 61.6, 4.8, 31.9, 6.4, 5.7, 3.8, 14.8, 7.1, 3.7, 3.7, 2.9, 6.3, 5.7, 2.8, 6. , 3.3, 11.7, 3.9, 4.5, 18.3, 20.9, 62.2, 8.2, 23. , 7.4, 3.1, 10. , 9.7, 3.3, 12.5, 3.8, 17.1, 6.7, 5.4, 4.4, 13.7, 16.9, 7.1, 3.5, 15.8, 5.9, 6.2, 3.2, 12. , 12.7, 2.8, 9.8, 6. , 98.9, 5.5, 14.3, 6.5, 18.8, 3.5, 4.2, 13.9, 8.2, 8.4, 2.6, 10.1, 3.2, 33.7, 17.2, 3.9, 6.8, 11.2, 5.2, 19.3, 2.3, 22.2, 6.9, 8.3, 4.9, 19.2, 7.6, 11.9, 10.8, 17.6, 20.5, 8.9, 11.3, 25.4], dtype=float32) - vy_stable_shift(mid_date)float32-74.2 -25.7 -28.5 ... -3.6 -10.8
- description :
- applied vy shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vy_stable_shift
- units :
- meter/year
array([-7.420e+01, -2.570e+01, -2.850e+01, -8.000e-01, -2.600e+00, 0.000e+00, -8.550e+01, 0.000e+00, 0.000e+00, -7.900e+00, 3.000e-01, -3.600e+00, -3.730e+01, -1.600e+00, -2.139e+02, -2.900e+00, 0.000e+00, 0.000e+00, 1.100e+00, 0.000e+00, 0.000e+00, 2.850e+01, 0.000e+00, -4.300e+00, 0.000e+00, -2.850e+01, 1.100e+00, 2.800e+00, 0.000e+00, -4.900e+00, -1.200e+00, 1.000e+00, -8.550e+01, 9.000e-01, 2.300e+00, -3.000e+00, -8.000e-01, 2.120e+01, -4.800e+00, 1.600e+00, 9.000e-01, 0.000e+00, -8.000e-01, 8.000e-01, 1.200e+00, -2.000e-01, -2.000e+00, -9.000e-01, -5.000e+00, 4.000e-01, -5.600e+00, 3.300e+00, 0.000e+00, -6.000e+00, 9.000e-01, -6.800e+00, -4.280e+01, -1.100e+00, -2.456e+02, -1.500e+00, -4.000e+00, -1.550e+01, -1.300e+00, 0.000e+00, -2.100e+00, 8.000e-01, 4.000e+00, 2.140e+01, 6.800e+00, 0.000e+00, -1.000e+00, -1.000e+00, -5.200e+00, -9.800e+00, 0.000e+00, 0.000e+00, 1.430e+01, -1.100e+00, 0.000e+00, -2.340e+01, 1.600e+00, -1.000e+00, 0.000e+00, -6.100e+00, -4.280e+01, -4.000e-01, 1.800e+00, -5.900e+00, 1.090e+01, 1.460e+01, 3.500e+00, -1.370e+01, 0.000e+00, 0.000e+00, 7.000e-01, -1.450e+01, -1.700e+00, 1.500e+00, 0.000e+00, 0.000e+00, ... 7.000e-01, 3.100e+00, -2.600e+00, -3.700e+00, 5.000e-01, 2.200e+00, 0.000e+00, -2.000e+00, -3.600e+00, -3.000e+00, 9.000e-01, 5.000e-01, -1.080e+01, 2.200e+00, -1.130e+01, -4.800e+00, -1.400e+00, -4.900e+00, -1.300e+00, -1.400e+00, -1.600e+00, 6.900e+00, 4.900e+00, 0.000e+00, -4.300e+00, -6.000e-01, -1.500e+00, 2.200e+00, 0.000e+00, -8.000e-01, 9.000e-01, -3.600e+00, -7.000e-01, -1.000e-01, -3.000e+00, -1.500e+00, 7.100e+00, 1.800e+00, -9.100e+00, 0.000e+00, -1.000e+00, 0.000e+00, -3.700e+00, -1.200e+00, -8.100e+00, -3.700e+00, -5.000e+00, 1.500e+00, -1.400e+00, 0.000e+00, -1.800e+00, -6.000e+00, -3.700e+00, 1.200e+00, 5.000e-01, -1.200e+00, 3.900e+00, -7.000e-01, -2.700e+00, -2.000e-01, 0.000e+00, -3.700e+00, 1.900e+00, -2.850e+01, -1.400e+00, -1.000e-01, -1.400e+00, -1.160e+01, 0.000e+00, -1.200e+00, 4.000e-01, -2.700e+00, -5.100e+00, -6.000e-01, -4.000e+00, -8.000e-01, -9.300e+00, -1.010e+01, 1.900e+00, -1.300e+00, -7.200e+00, -2.100e+00, 5.000e+00, -6.000e-01, 6.100e+00, 2.100e+00, -1.400e+01, 1.500e+00, -1.080e+01, -6.700e+00, -1.200e+01, -4.400e+00, -1.210e+01, 2.700e+00, -3.300e+00, -3.600e+00, -1.080e+01], dtype=float32) - vy_stable_shift_slow(mid_date)float32-73.8 -25.7 -28.5 ... -3.6 -10.7
- description :
- vy shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vy_stable_shift_slow
- units :
- meter/year
array([-7.380e+01, -2.570e+01, -2.850e+01, -7.000e-01, -2.600e+00, 0.000e+00, -8.550e+01, 0.000e+00, 0.000e+00, -7.900e+00, 3.000e-01, -3.600e+00, -3.720e+01, -1.600e+00, -2.139e+02, -2.900e+00, 0.000e+00, 0.000e+00, 1.200e+00, 0.000e+00, 0.000e+00, 2.850e+01, 0.000e+00, -4.300e+00, 0.000e+00, -2.850e+01, 1.100e+00, 2.800e+00, 0.000e+00, -4.900e+00, -1.200e+00, 1.000e+00, -8.550e+01, 9.000e-01, 2.300e+00, -3.000e+00, -8.000e-01, 2.110e+01, -4.800e+00, 1.600e+00, 9.000e-01, 0.000e+00, -8.000e-01, 8.000e-01, 1.200e+00, -2.000e-01, -2.000e+00, -9.000e-01, -5.000e+00, 4.000e-01, -5.700e+00, 3.300e+00, 0.000e+00, -6.000e+00, 9.000e-01, -6.800e+00, -4.280e+01, -1.100e+00, -2.458e+02, -1.500e+00, -4.000e+00, -1.550e+01, -1.300e+00, 0.000e+00, -2.100e+00, 8.000e-01, 4.000e+00, 2.140e+01, 6.800e+00, 0.000e+00, -1.000e+00, -1.000e+00, -5.200e+00, -9.800e+00, 0.000e+00, 0.000e+00, 1.430e+01, -1.100e+00, 0.000e+00, -2.340e+01, 1.600e+00, -1.000e+00, 0.000e+00, -6.100e+00, -4.280e+01, -5.000e-01, 1.800e+00, -5.900e+00, 1.100e+01, 1.470e+01, 3.500e+00, -1.380e+01, 0.000e+00, 0.000e+00, 7.000e-01, -1.450e+01, -1.800e+00, 1.500e+00, 0.000e+00, 0.000e+00, ... 7.000e-01, 3.100e+00, -2.500e+00, -3.700e+00, 5.000e-01, 2.200e+00, 0.000e+00, -2.000e+00, -3.600e+00, -3.000e+00, 9.000e-01, 5.000e-01, -1.070e+01, 2.200e+00, -1.140e+01, -4.200e+00, -1.400e+00, -4.800e+00, -1.300e+00, -1.400e+00, -1.600e+00, 7.100e+00, 4.900e+00, 0.000e+00, -4.300e+00, -6.000e-01, -1.500e+00, 2.200e+00, 0.000e+00, -8.000e-01, 9.000e-01, -3.600e+00, -7.000e-01, -1.000e-01, -3.000e+00, -1.500e+00, 7.500e+00, 1.800e+00, -9.100e+00, 0.000e+00, -1.000e+00, 0.000e+00, -3.700e+00, -1.200e+00, -8.100e+00, -3.700e+00, -5.000e+00, 1.500e+00, -1.400e+00, 0.000e+00, -1.900e+00, -6.000e+00, -3.700e+00, 1.200e+00, 6.000e-01, -1.200e+00, 3.900e+00, -7.000e-01, -2.700e+00, -2.000e-01, 0.000e+00, -3.700e+00, 1.900e+00, -2.850e+01, -1.400e+00, -1.000e-01, -1.400e+00, -1.150e+01, 0.000e+00, -1.200e+00, 4.000e-01, -2.700e+00, -5.100e+00, -6.000e-01, -4.100e+00, -8.000e-01, -9.300e+00, -1.010e+01, 1.900e+00, -1.300e+00, -7.100e+00, -2.100e+00, 5.000e+00, -6.000e-01, 6.000e+00, 2.100e+00, -1.400e+01, 1.500e+00, -1.070e+01, -6.700e+00, -1.200e+01, -4.300e+00, -1.200e+01, 2.800e+00, -3.300e+00, -3.600e+00, -1.070e+01], dtype=float32) - vy_stable_shift_stationary(mid_date)float32-74.2 -25.7 -28.5 ... -3.6 -10.8
- description :
- vy shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vy_stable_shift_stationary
- units :
- meter/year
array([-7.420e+01, -2.570e+01, -2.850e+01, -8.000e-01, -2.600e+00, 0.000e+00, -8.550e+01, 0.000e+00, 0.000e+00, -7.900e+00, 3.000e-01, -3.600e+00, -3.730e+01, -1.600e+00, -2.139e+02, -2.900e+00, 0.000e+00, 0.000e+00, 1.100e+00, 0.000e+00, 0.000e+00, 2.850e+01, 0.000e+00, -4.300e+00, 0.000e+00, -2.850e+01, 1.100e+00, 2.800e+00, 0.000e+00, -4.900e+00, -1.200e+00, 1.000e+00, -8.550e+01, 9.000e-01, 2.300e+00, -3.000e+00, -8.000e-01, 2.120e+01, -4.800e+00, 1.600e+00, 9.000e-01, 0.000e+00, -8.000e-01, 8.000e-01, 1.200e+00, -2.000e-01, -2.000e+00, -9.000e-01, -5.000e+00, 4.000e-01, -5.600e+00, 3.300e+00, 0.000e+00, -6.000e+00, 9.000e-01, -6.800e+00, -4.280e+01, -1.100e+00, -2.456e+02, -1.500e+00, -4.000e+00, -1.550e+01, -1.300e+00, 0.000e+00, -2.100e+00, 8.000e-01, 4.000e+00, 2.140e+01, 6.800e+00, 0.000e+00, -1.000e+00, -1.000e+00, -5.200e+00, -9.800e+00, 0.000e+00, 0.000e+00, 1.430e+01, -1.100e+00, 0.000e+00, -2.340e+01, 1.600e+00, -1.000e+00, 0.000e+00, -6.100e+00, -4.280e+01, -4.000e-01, 1.800e+00, -5.900e+00, 1.090e+01, 1.460e+01, 3.500e+00, -1.370e+01, 0.000e+00, 0.000e+00, 7.000e-01, -1.450e+01, -1.700e+00, 1.500e+00, 0.000e+00, 0.000e+00, ... 7.000e-01, 3.100e+00, -2.600e+00, -3.700e+00, 5.000e-01, 2.200e+00, 0.000e+00, -2.000e+00, -3.600e+00, -3.000e+00, 9.000e-01, 5.000e-01, -1.080e+01, 2.200e+00, -1.130e+01, -4.800e+00, -1.400e+00, -4.900e+00, -1.300e+00, -1.400e+00, -1.600e+00, 6.900e+00, 4.900e+00, 0.000e+00, -4.300e+00, -6.000e-01, -1.500e+00, 2.200e+00, 0.000e+00, -8.000e-01, 9.000e-01, -3.600e+00, -7.000e-01, -1.000e-01, -3.000e+00, -1.500e+00, 7.100e+00, 1.800e+00, -9.100e+00, 0.000e+00, -1.000e+00, 0.000e+00, -3.700e+00, -1.200e+00, -8.100e+00, -3.700e+00, -5.000e+00, 1.500e+00, -1.400e+00, 0.000e+00, -1.800e+00, -6.000e+00, -3.700e+00, 1.200e+00, 5.000e-01, -1.200e+00, 3.900e+00, -7.000e-01, -2.700e+00, -2.000e-01, 0.000e+00, -3.700e+00, 1.900e+00, -2.850e+01, -1.400e+00, -1.000e-01, -1.400e+00, -1.160e+01, 0.000e+00, -1.200e+00, 4.000e-01, -2.700e+00, -5.100e+00, -6.000e-01, -4.000e+00, -8.000e-01, -9.300e+00, -1.010e+01, 1.900e+00, -1.300e+00, -7.200e+00, -2.100e+00, 5.000e+00, -6.000e-01, 6.100e+00, 2.100e+00, -1.400e+01, 1.500e+00, -1.080e+01, -6.700e+00, -1.200e+01, -4.400e+00, -1.210e+01, 2.700e+00, -3.300e+00, -3.600e+00, -1.080e+01], dtype=float32)
- mid_datePandasIndex
PandasIndex(DatetimeIndex(['2017-12-25 04:11:40.527109888', '2018-12-12 04:08:03.179142912', '2018-12-04 04:08:17.320696064', '2017-07-18 04:11:34.949195008', '2018-07-13 04:08:04.816436992', '2019-07-04 04:10:27.618160896', '2017-01-23 04:11:33.121705984', '2017-07-30 04:10:28.475568128', '2017-11-07 04:11:55.447443968', '2017-12-01 04:11:43.316209920', ... '2018-03-15 04:08:53.730741248', '2018-06-19 04:09:27.910211072', '2018-04-08 04:08:58.818386944', '2017-12-09 04:11:12.435494912', '2018-03-31 04:10:01.464065024', '2018-06-11 04:09:32.921265664', '2017-09-12 04:11:46.053865984', '2017-06-24 04:11:18.708142080', '2017-05-27 04:10:08.145324032', '2017-05-07 04:11:30.865388288'], dtype='datetime64[ns]', name='mid_date', length=662, freq=None)) - xPandasIndex
PandasIndex(Index([700252.5, 700372.5, 700492.5, 700612.5, 700732.5, 700852.5, 700972.5, 701092.5, 701212.5, 701332.5, 701452.5, 701572.5, 701692.5, 701812.5, 701932.5, 702052.5, 702172.5, 702292.5, 702412.5, 702532.5, 702652.5, 702772.5, 702892.5, 703012.5, 703132.5, 703252.5, 703372.5, 703492.5, 703612.5, 703732.5, 703852.5, 703972.5, 704092.5, 704212.5, 704332.5, 704452.5, 704572.5, 704692.5, 704812.5, 704932.5, 705052.5, 705172.5, 705292.5, 705412.5, 705532.5, 705652.5, 705772.5, 705892.5, 706012.5, 706132.5, 706252.5, 706372.5, 706492.5, 706612.5, 706732.5, 706852.5, 706972.5, 707092.5, 707212.5, 707332.5, 707452.5, 707572.5, 707692.5, 707812.5, 707932.5, 708052.5, 708172.5, 708292.5, 708412.5, 708532.5, 708652.5, 708772.5, 708892.5], dtype='float64', name='x')) - yPandasIndex
PandasIndex(Index([3394627.5, 3394507.5, 3394387.5, 3394267.5, 3394147.5, 3394027.5, 3393907.5, 3393787.5, 3393667.5, 3393547.5, 3393427.5, 3393307.5, 3393187.5, 3393067.5, 3392947.5, 3392827.5, 3392707.5, 3392587.5, 3392467.5, 3392347.5, 3392227.5, 3392107.5, 3391987.5, 3391867.5, 3391747.5, 3391627.5, 3391507.5, 3391387.5, 3391267.5, 3391147.5, 3391027.5, 3390907.5, 3390787.5, 3390667.5, 3390547.5, 3390427.5, 3390307.5, 3390187.5, 3390067.5, 3389947.5, 3389827.5, 3389707.5, 3389587.5, 3389467.5, 3389347.5, 3389227.5, 3389107.5, 3388987.5, 3388867.5, 3388747.5, 3388627.5, 3388507.5, 3388387.5, 3388267.5, 3388147.5, 3388027.5, 3387907.5, 3387787.5, 3387667.5, 3387547.5, 3387427.5, 3387307.5, 3387187.5, 3387067.5], dtype='float64', name='y'))
- Conventions :
- CF-1.8
- GDAL_AREA_OR_POINT :
- Area
- author :
- ITS_LIVE, a NASA MEaSUREs project (its-live.jpl.nasa.gov)
- autoRIFT_parameter_file :
- http://its-live-data.s3.amazonaws.com/autorift_parameters/v001/autorift_landice_0120m.shp
- datacube_software_version :
- 1.0
- date_created :
- 25-Sep-2023 22:00:23
- date_updated :
- 25-Sep-2023 22:00:23
- geo_polygon :
- [[95.06959008486952, 29.814255053135895], [95.32812062059084, 29.809951334550703], [95.58659184122865, 29.80514261876954], [95.84499718862224, 29.7998293459177], [96.10333011481168, 29.79401200205343], [96.11032804508507, 30.019297601073085], [96.11740568350054, 30.244573983323825], [96.12456379063154, 30.469841094022847], [96.1318031397002, 30.695098878594504], [95.87110827645229, 30.70112924501256], [95.61033817656023, 30.7066371044805], [95.34949964126946, 30.711621947056347], [95.08859948278467, 30.716083310981194], [95.08376623410525, 30.49063893600811], [95.07898726183609, 30.26518607254204], [95.0742620484426, 30.039724763743482], [95.06959008486952, 29.814255053135895]]
- institution :
- NASA Jet Propulsion Laboratory (JPL), California Institute of Technology
- latitude :
- 30.26
- longitude :
- 95.6
- proj_polygon :
- [[700000, 3300000], [725000.0, 3300000.0], [750000.0, 3300000.0], [775000.0, 3300000.0], [800000, 3300000], [800000.0, 3325000.0], [800000.0, 3350000.0], [800000.0, 3375000.0], [800000, 3400000], [775000.0, 3400000.0], [750000.0, 3400000.0], [725000.0, 3400000.0], [700000, 3400000], [700000.0, 3375000.0], [700000.0, 3350000.0], [700000.0, 3325000.0], [700000, 3300000]]
- projection :
- 32646
- s3 :
- s3://its-live-data/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.zarr
- skipped_granules :
- s3://its-live-data/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.json
- time_standard_img1 :
- UTC
- time_standard_img2 :
- UTC
- title :
- ITS_LIVE datacube of image pair velocities
- url :
- https://its-live-data.s3.amazonaws.com/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.zarr
dataset.where() at first seems appropriate to use for kind of operation but there’s actually an easier way. Because we are selecting along a single dimension (mid_date), we can use xarray’s .sel() method instead. This is more efficient and integrates with dask arrays more smoothly.
l8_condition = sample_glacier_raster.satellite_img1 == '8'
l8_subset = sample_glacier_raster.sel(mid_date=l8_condition)
l8_subset
<xarray.Dataset>
Dimensions: (mid_date: 662, y: 64, x: 73)
Coordinates:
* mid_date (mid_date) datetime64[ns] 2017-12-25T04:11:40...
* x (x) float64 7.003e+05 7.004e+05 ... 7.089e+05
* y (y) float64 3.395e+06 3.395e+06 ... 3.387e+06
mapping int64 0
Data variables: (12/59)
M11 (mid_date, y, x) float32 nan nan nan ... nan nan
M11_dr_to_vr_factor (mid_date) float32 nan nan nan ... nan nan nan
M12 (mid_date, y, x) float32 nan nan nan ... nan nan
M12_dr_to_vr_factor (mid_date) float32 nan nan nan ... nan nan nan
acquisition_date_img1 (mid_date) datetime64[ns] 2017-12-21T04:10:40...
acquisition_date_img2 (mid_date) datetime64[ns] 2017-12-29T04:12:40...
... ...
vy_error_modeled (mid_date) float32 1.163e+03 232.7 ... 166.2
vy_error_slow (mid_date) float32 112.5 37.6 54.1 ... 11.3 25.4
vy_error_stationary (mid_date) float32 112.5 37.6 54.2 ... 11.3 25.4
vy_stable_shift (mid_date) float32 -74.2 -25.7 ... -3.6 -10.8
vy_stable_shift_slow (mid_date) float32 -73.8 -25.7 ... -3.6 -10.7
vy_stable_shift_stationary (mid_date) float32 -74.2 -25.7 ... -3.6 -10.8
Attributes: (12/19)
Conventions: CF-1.8
GDAL_AREA_OR_POINT: Area
author: ITS_LIVE, a NASA MEaSUREs project (its-live.j...
autoRIFT_parameter_file: http://its-live-data.s3.amazonaws.com/autorif...
datacube_software_version: 1.0
date_created: 25-Sep-2023 22:00:23
... ...
s3: s3://its-live-data/datacubes/v2/N30E090/ITS_L...
skipped_granules: s3://its-live-data/datacubes/v2/N30E090/ITS_L...
time_standard_img1: UTC
time_standard_img2: UTC
title: ITS_LIVE datacube of image pair velocities
url: https://its-live-data.s3.amazonaws.com/datacu...- mid_date: 662
- y: 64
- x: 73
- mid_date(mid_date)datetime64[ns]2017-12-25T04:11:40.527109888 .....
- description :
- midpoint of image 1 and image 2 acquisition date and time with granule's centroid longitude and latitude as microseconds
- standard_name :
- image_pair_center_date_with_time_separation
array(['2017-12-25T04:11:40.527109888', '2018-12-12T04:08:03.179142912', '2018-12-04T04:08:17.320696064', ..., '2017-06-24T04:11:18.708142080', '2017-05-27T04:10:08.145324032', '2017-05-07T04:11:30.865388288'], dtype='datetime64[ns]') - x(x)float647.003e+05 7.004e+05 ... 7.089e+05
- description :
- x coordinate of projection
- standard_name :
- projection_x_coordinate
- axis :
- X
- long_name :
- x coordinate of projection
- units :
- metre
array([700252.5, 700372.5, 700492.5, 700612.5, 700732.5, 700852.5, 700972.5, 701092.5, 701212.5, 701332.5, 701452.5, 701572.5, 701692.5, 701812.5, 701932.5, 702052.5, 702172.5, 702292.5, 702412.5, 702532.5, 702652.5, 702772.5, 702892.5, 703012.5, 703132.5, 703252.5, 703372.5, 703492.5, 703612.5, 703732.5, 703852.5, 703972.5, 704092.5, 704212.5, 704332.5, 704452.5, 704572.5, 704692.5, 704812.5, 704932.5, 705052.5, 705172.5, 705292.5, 705412.5, 705532.5, 705652.5, 705772.5, 705892.5, 706012.5, 706132.5, 706252.5, 706372.5, 706492.5, 706612.5, 706732.5, 706852.5, 706972.5, 707092.5, 707212.5, 707332.5, 707452.5, 707572.5, 707692.5, 707812.5, 707932.5, 708052.5, 708172.5, 708292.5, 708412.5, 708532.5, 708652.5, 708772.5, 708892.5]) - y(y)float643.395e+06 3.395e+06 ... 3.387e+06
- description :
- y coordinate of projection
- standard_name :
- projection_y_coordinate
- axis :
- Y
- long_name :
- y coordinate of projection
- units :
- metre
array([3394627.5, 3394507.5, 3394387.5, 3394267.5, 3394147.5, 3394027.5, 3393907.5, 3393787.5, 3393667.5, 3393547.5, 3393427.5, 3393307.5, 3393187.5, 3393067.5, 3392947.5, 3392827.5, 3392707.5, 3392587.5, 3392467.5, 3392347.5, 3392227.5, 3392107.5, 3391987.5, 3391867.5, 3391747.5, 3391627.5, 3391507.5, 3391387.5, 3391267.5, 3391147.5, 3391027.5, 3390907.5, 3390787.5, 3390667.5, 3390547.5, 3390427.5, 3390307.5, 3390187.5, 3390067.5, 3389947.5, 3389827.5, 3389707.5, 3389587.5, 3389467.5, 3389347.5, 3389227.5, 3389107.5, 3388987.5, 3388867.5, 3388747.5, 3388627.5, 3388507.5, 3388387.5, 3388267.5, 3388147.5, 3388027.5, 3387907.5, 3387787.5, 3387667.5, 3387547.5, 3387427.5, 3387307.5, 3387187.5, 3387067.5]) - mapping()int640
- crs_wkt :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- WGS 84
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- WGS 84 / UTM zone 46N
- grid_mapping_name :
- transverse_mercator
- latitude_of_projection_origin :
- 0.0
- longitude_of_central_meridian :
- 93.0
- false_easting :
- 500000.0
- false_northing :
- 0.0
- scale_factor_at_central_meridian :
- 0.9996
- spatial_ref :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- GeoTransform :
- 700192.5 120.0 0.0 3394687.5 0.0 -120.0
array(0)
- M11(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- conversion matrix element (1st row, 1st column) that can be multiplied with vx to give range pixel displacement dr (see Eq. A18 in https://www.mdpi.com/2072-4292/13/4/749)
- grid_mapping :
- mapping
- standard_name :
- conversion_matrix_element_11
- units :
- pixel/(meter/year)
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - M11_dr_to_vr_factor(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- multiplicative factor that converts slant range pixel displacement dr to slant range velocity vr
- standard_name :
- M11_dr_to_vr_factor
- units :
- meter/(year*pixel)
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - M12(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- conversion matrix element (1st row, 2nd column) that can be multiplied with vy to give range pixel displacement dr (see Eq. A18 in https://www.mdpi.com/2072-4292/13/4/749)
- grid_mapping :
- mapping
- standard_name :
- conversion_matrix_element_12
- units :
- pixel/(meter/year)
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - M12_dr_to_vr_factor(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- multiplicative factor that converts slant range pixel displacement dr to slant range velocity vr
- standard_name :
- M12_dr_to_vr_factor
- units :
- meter/(year*pixel)
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - acquisition_date_img1(mid_date)datetime64[ns]2017-12-21T04:10:40.253580032 .....
- description :
- acquisition date and time of image 1
- standard_name :
- image1_acquition_date
array(['2017-12-21T04:10:40.253580032', '2018-11-22T04:10:24.234354944', '2018-11-22T04:10:24.234354944', '2017-02-04T04:10:29.099783936', '2018-01-22T04:10:27.510945024', '2018-11-22T04:10:24.234354944', '2017-01-19T04:10:36.447260928', '2017-02-04T04:10:29.099783936', '2017-11-03T04:10:45.832015872', '2017-11-03T04:10:45.832015872', '2017-02-04T04:10:29.099783936', '2017-12-21T04:10:40.253580032', '2018-11-22T04:10:24.234354944', '2018-01-22T04:10:27.510945024', '2018-11-22T04:10:24.234354944', '2017-12-21T04:10:40.253580032', '2017-02-04T04:10:29.099783936', '2017-01-19T04:10:36.447260928', '2018-01-22T04:10:27.510945024', '2017-01-19T04:10:36.447260928', '2017-02-04T04:10:29.099783936', '2017-02-04T04:10:29.099783936', '2018-01-22T04:10:27.510945024', '2017-11-03T04:10:45.832015872', '2017-11-03T04:10:45.832015872', '2018-12-08T04:10:21.702228992', '2017-02-04T04:10:29.099783936', '2018-01-22T04:10:27.510945024', '2016-10-31T04:10:49.197186048', '2018-01-22T04:10:27.510945024', '2016-10-31T04:10:49.197186048', '2017-01-19T04:10:36.447260928', '2018-12-08T04:10:21.702228992', '2017-01-19T04:10:36.447260928', '2017-12-21T04:10:40.253580032', '2017-11-03T04:10:45.832015872', '2017-12-21T04:10:40.253580032', '2017-01-19T04:10:36.447260928', '2018-01-22T04:10:27.510945024', '2019-01-09T04:10:19.605915904', ... '2017-07-30T04:10:25.156854016', '2017-07-30T04:10:25.156854016', '2017-07-30T04:10:25.156854016', '2017-07-30T04:10:25.156854016', '2018-02-07T04:10:19.247780096', '2016-11-16T04:10:48.428282112', '2016-10-15T04:10:47.896870912', '2017-07-30T04:10:25.156854016', '2018-03-27T04:09:57.437323008', '2017-07-30T04:10:25.156854016', '2017-04-09T04:09:59.003422976', '2018-02-07T04:10:19.247780096', '2017-04-09T04:09:59.003422976', '2016-10-15T04:10:47.896870912', '2017-07-30T04:10:25.156854016', '2017-07-30T04:10:25.156854016', '2017-07-30T04:10:25.156854016', '2017-09-16T04:10:35.331774976', '2017-10-18T04:10:46.076395008', '2017-07-30T04:10:25.156854016', '2016-10-15T04:10:47.896870912', '2017-11-19T04:10:41.686725376', '2017-04-09T04:09:59.003422976', '2018-05-30T04:09:17.034597888', '2017-04-09T04:09:59.003422976', '2017-07-14T04:10:16.946407936', '2017-04-09T04:09:59.003422976', '2017-09-16T04:10:35.331774976', '2017-07-30T04:10:25.156854016', '2018-05-14T04:09:29.903631104', '2017-09-16T04:10:35.331774976', '2017-09-16T04:10:35.331774976', '2017-12-05T04:10:37.029957888', '2018-04-28T04:09:39.925913088', '2017-07-30T04:10:25.156854016', '2016-10-15T04:10:47.896870912', '2017-04-09T04:09:59.003422976', '2017-04-09T04:09:59.003422976'], dtype='datetime64[ns]') - acquisition_date_img2(mid_date)datetime64[ns]2017-12-29T04:12:40.458198016 .....
- description :
- acquisition date and time of image 2
- standard_name :
- image2_acquition_date
array(['2017-12-29T04:12:40.458198016', '2019-01-01T04:05:41.761686272', '2018-12-16T04:06:10.044793088', '2017-12-29T04:12:40.458198016', '2019-01-01T04:05:41.761686272', '2020-02-13T04:10:30.639724032', '2017-01-27T04:12:29.455911936', '2018-01-22T04:10:27.510945024', '2017-11-11T04:13:04.720666112', '2017-12-29T04:12:40.458198016', '2018-02-15T04:11:59.198033920', '2019-01-01T04:05:41.761686272', '2019-01-17T04:05:11.586401024', '2018-12-16T04:06:10.044793088', '2018-11-30T04:06:36.228204288', '2018-12-16T04:06:10.044793088', '2017-12-21T04:10:40.253580032', '2017-12-29T04:12:40.458198016', '2018-02-15T04:11:59.198033920', '2018-01-22T04:10:27.510945024', '2017-11-11T04:13:04.720666112', '2017-02-28T04:12:32.528041984', '2018-11-22T04:10:24.234354944', '2018-01-22T04:10:27.510945024', '2017-12-21T04:10:40.253580032', '2019-01-01T04:05:41.761686272', '2017-11-03T04:10:45.832015872', '2019-06-02T04:10:12.332978176', '2017-11-11T04:13:04.720666112', '2019-01-17T04:05:11.586401024', '2017-12-29T04:12:40.458198016', '2017-12-21T04:10:40.253580032', '2018-12-16T04:06:10.044793088', '2018-02-15T04:11:59.198033920', '2019-06-02T04:10:12.332978176', '2019-01-01T04:05:41.761686272', '2018-02-15T04:11:59.198033920', '2017-02-28T04:12:32.528041984', '2018-11-30T04:06:36.228204288', '2020-02-29T04:10:26.243158016', ... '2017-11-19T04:10:41.686725376', '2018-05-30T04:09:17.034597888', '2018-01-30T04:12:11.667300096', '2018-04-04T04:11:23.527504896', '2018-03-03T04:11:49.197383936', '2018-03-03T04:11:49.197383936', '2017-06-04T04:13:02.386535936', '2018-11-30T04:06:36.228204288', '2018-07-25T04:09:25.555763200', '2018-05-22T04:10:35.049019904', '2018-05-22T04:10:35.049019904', '2018-10-29T04:07:21.963168256', '2017-10-26T04:13:06.609417984', '2017-04-09T04:09:59.003422976', '2019-01-25T04:10:15.711925760', '2018-01-14T04:12:27.084400896', '2019-01-09T04:10:19.605915904', '2017-10-26T04:13:06.609417984', '2018-03-03T04:11:49.197383936', '2018-07-25T04:09:25.555763200', '2017-07-14T04:10:16.946407936', '2018-07-25T04:09:25.555763200', '2018-03-03T04:11:49.197383936', '2018-07-25T04:09:25.555763200', '2018-09-19T04:10:06.348390144', '2017-10-26T04:13:06.609417984', '2017-09-16T04:10:35.331774976', '2018-11-30T04:06:36.228204288', '2018-10-29T04:07:21.963168256', '2018-07-25T04:09:25.555763200', '2018-10-29T04:07:21.963168256', '2018-03-03T04:11:49.197383936', '2018-07-25T04:09:25.555763200', '2018-07-25T04:09:25.555763200', '2017-10-26T04:13:06.609417984', '2018-03-03T04:11:49.197383936', '2017-07-14T04:10:16.946407936', '2017-06-04T04:13:02.386535936'], dtype='datetime64[ns]') - autoRIFT_software_version(mid_date)object'1.5.0' '1.5.0' ... '1.5.0' '1.5.0'
- description :
- version of autoRIFT software
- standard_name :
- autoRIFT_software_version
array(['1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', ... '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0'], dtype=object) - chip_size_height(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- chip_size_coordinates :
- Optical data: chip_size_coordinates = 'image projection geometry: width = x, height = y'. Radar data: chip_size_coordinates = 'radar geometry: width = range, height = azimuth'
- description :
- height of search template (chip)
- grid_mapping :
- mapping
- standard_name :
- chip_size_height
- units :
- m
- y_pixel_size :
- 10.0
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - chip_size_width(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- chip_size_coordinates :
- Optical data: chip_size_coordinates = 'image projection geometry: width = x, height = y'. Radar data: chip_size_coordinates = 'radar geometry: width = range, height = azimuth'
- description :
- width of search template (chip)
- grid_mapping :
- mapping
- standard_name :
- chip_size_width
- units :
- m
- x_pixel_size :
- 10.0
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - date_center(mid_date)datetime64[ns]2017-12-25T04:11:40.355888896 .....
- description :
- midpoint of image 1 and image 2 acquisition date
- standard_name :
- image_pair_center_date
array(['2017-12-25T04:11:40.355888896', '2018-12-12T04:08:02.998021120', '2018-12-04T04:08:17.139574016', '2017-07-18T04:11:34.778990848', '2018-07-13T04:08:04.636314880', '2019-07-04T04:10:27.437039104', '2017-01-23T04:11:32.951587072', '2017-07-30T04:10:28.305363968', '2017-11-07T04:11:55.276340992', '2017-12-01T04:11:43.145106944', '2017-08-11T04:11:14.148909056', '2018-06-27T04:08:11.007632896', '2018-12-20T04:07:47.910377984', '2018-07-05T04:08:18.777868800', '2018-11-26T04:08:30.231279104', '2018-06-19T04:08:25.149186048', '2017-07-14T04:10:34.676681984', '2017-07-10T04:11:38.452729088', '2018-02-03T04:11:13.354489088', '2017-07-22T04:10:31.979102976', '2017-06-24T04:11:46.910224896', '2017-02-16T04:11:30.813913088', '2018-06-23T04:10:25.872649728', '2017-12-13T04:10:36.671480064', '2017-11-27T04:10:43.042798080', '2018-12-20T04:08:01.731956992', '2017-06-20T04:10:37.465900032', '2018-09-27T04:10:19.921960960', '2017-05-07T04:11:56.958926336', '2018-07-21T04:07:49.548673024', '2017-05-31T04:11:44.827692032', '2017-07-06T04:10:38.350421248', '2018-12-12T04:08:15.873510912', '2017-08-03T04:11:17.822647296', '2018-09-11T04:10:26.293278976', '2018-06-03T04:08:13.796850944', '2018-01-18T04:11:19.725807104', '2017-02-08T04:11:34.487651328', '2018-06-27T04:08:31.869574912', '2019-08-05T04:10:22.924537088', ... '2017-09-24T04:10:33.421789952', '2017-12-29T04:09:51.095726336', '2017-10-30T04:11:18.412077056', '2017-12-01T04:10:54.342180096', '2018-02-19T04:11:04.222582016', '2017-07-10T04:11:18.812833024', '2017-02-08T04:11:55.141702912', '2018-03-31T04:08:30.692528640', '2018-05-26T04:09:41.496542976', '2017-12-25T04:10:30.102937088', '2017-10-30T04:10:17.026221056', '2018-06-19T04:08:50.605474048', '2017-07-18T04:11:32.806420992', '2017-01-11T04:10:23.450147072', '2018-04-28T04:10:20.434390016', '2017-10-22T04:11:26.120627968', '2018-04-20T04:10:22.381384960', '2017-10-06T04:11:50.970597120', '2017-12-25T04:11:17.636889344', '2018-01-26T04:09:55.356307968', '2017-02-28T04:10:32.421638912', '2018-03-23T04:10:03.621243904', '2017-09-20T04:10:54.100402944', '2018-06-27T04:09:21.295180032', '2017-12-29T04:10:02.675906816', '2017-09-04T04:11:41.777913344', '2017-06-28T04:10:17.167599104', '2018-04-24T04:08:35.779988992', '2018-03-15T04:08:53.560011008', '2018-06-19T04:09:27.729697024', '2018-04-08T04:08:58.647471104', '2017-12-09T04:11:12.264579072', '2018-03-31T04:10:01.292859904', '2018-06-11T04:09:32.740837888', '2017-09-12T04:11:45.883136000', '2017-06-24T04:11:18.547127040', '2017-05-27T04:10:07.974915072', '2017-05-07T04:11:30.694979072'], dtype='datetime64[ns]') - date_dt(mid_date)timedelta64[ns]8 days 00:02:00.217895504 ... 56...
- description :
- time separation between acquisition of image 1 and image 2
- standard_name :
- image_pair_time_separation
array([ 691320217895504, 3455717541503909, 2073345886230468, 28339331835937495, 29721315234375000, 38707205273437495, 691313049316405, 30412797363281252, 691338922119144, 4838514697265621, 32486489648437495, 32486102050781252, 4838087219238279, 28338941601562504, 690972006225585, 31103731054687495, 27648010546875000, 29721723925781252, 2073691625976558, 31795192089843747, 24192155566406252, 2073723431396486, 26265597363281252, 6911981542968747, 4147194396972657, 2073320013427738, 23500815820312504, 42854384179687495, 32486534472656252, 31103683593750000, 36633710742187495, 29030402636718747, 690948358154297, 33868881738281252, 45619173632812504, 36633296777343747, 4838479101562504, 3456116015625000, 26956567968750000, 35942407910156252, 34560010546875000, 40780871191406252, 38707178906250000, 37324807910156252, 24883210546875000, 33177578906250000, 35250923144531252, 31795221093750000, 33868549511718747, 25574547656250000, 20736026367187495, 35942368359375000, 8985673168945315, 33868470410156252, 35251268554687495, 29721354785156252, 3455689855957027, 26956942382812504, 690891998291017, 29030423730468747, ... 8985667236328126, 20735968359375000, 35942357812500000, 12441626367187495, 15897730517578126, 29030386816406252, 25574175878906252, 46310088867187495, 11750546337890621, 19353581542968747, 26265621093750000, 45619294921875000, 16588856689453126, 14515314697265621, 24192147656250000, 24883163085937495, 17280134472656252, 38016065917968747, 20735972314453126, 42854397363281252, 11059211865234378, 9676816479492189, 26265531445312504, 15897706787109378, 21427258007812504, 2073689978027342, 40780860644531252, 20044934472656252, 42162970605468747, 10367968359375000, 25574410546875000, 35251236914062504, 22809423339843747, 17280187207031252, 15206351220703126, 47001589453125000, 14515321289062504, 45619194726562504, 3456151281738279, 11750463281250000, 31103939355468747, 23500768359375000, 21427123535156252, 28339310742187495, 4838408569335936, 45619205273437495, 8985769409179684, 13824036914062504, 38015760058593747, 39398218066406252, 6220795385742189, 35251007519531252, 14515273828125000, 20044728808593747, 7603185498046873, 7603361499023441, 43545660644531252, 8294417797851558, 4838583251953126], dtype='timedelta64[ns]') - floatingice(y, x, mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- floating ice mask, 0 = non-floating-ice, 1 = floating-ice
- flag_meanings :
- non-ice ice
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- floating ice mask
- url :
- https://its-live-data.s3.amazonaws.com/autorift_parameters/v001/N46_0120m_floatingice.tif
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - granule_url(mid_date)object'https://its-live-data.s3.amazon...
- description :
- original granule URL
- standard_name :
- granule_url
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'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170730_20200903_02_T1_X_LE07_L1TP_135039_20180725_20200828_02_T1_G0120V02_P008.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20161015_20200905_02_T1_X_LC08_L1TP_135039_20170714_20200903_02_T1_G0120V02_P007.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20171119_20200902_02_T1_X_LE07_L1TP_135039_20180725_20200828_02_T1_G0120V02_P008.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170409_20200904_02_T1_X_LE07_L1TP_135039_20180303_20200829_02_T1_G0120V02_P007.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20180530_20200831_02_T1_X_LE07_L1TP_135039_20180725_20200828_02_T1_G0120V02_P007.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170409_20200904_02_T1_X_LC08_L1TP_135039_20180919_20200830_02_T1_G0120V02_P006.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170714_20200903_02_T1_X_LE07_L1TP_135039_20171026_20200830_02_T1_G0120V02_P007.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170409_20200904_02_T1_X_LC08_L1TP_135039_20170916_20200903_02_T1_G0120V02_P007.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170916_20200903_02_T1_X_LE07_L1TP_135039_20181130_20200827_02_T1_G0120V02_P007.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N20E090/LC08_L1TP_135039_20170730_20200903_02_T1_X_LE07_L1TP_135039_20181029_20200827_02_T1_G0120V02_P007.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20180514_20200901_02_T1_X_LE07_L1TP_135039_20180725_20200828_02_T1_G0120V02_P006.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170916_20200903_02_T1_X_LE07_L1TP_135039_20181029_20200827_02_T1_G0120V02_P005.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170916_20200903_02_T1_X_LE07_L1TP_135039_20180303_20200829_02_T1_G0120V02_P004.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20171205_20200902_02_T1_X_LE07_L1TP_135039_20180725_20200828_02_T1_G0120V02_P005.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20180428_20200901_02_T1_X_LE07_L1TP_135039_20180725_20200828_02_T1_G0120V02_P003.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170730_20200903_02_T1_X_LE07_L1TP_135039_20171026_20200830_02_T1_G0120V02_P003.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20161015_20200905_02_T1_X_LE07_L1TP_135039_20180303_20200829_02_T1_G0120V02_P003.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170409_20200904_02_T1_X_LC08_L1TP_135039_20170714_20200903_02_T1_G0120V02_P003.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/landsatOLI/v02/N30E090/LC08_L1TP_135039_20170409_20200904_02_T1_X_LE07_L1TP_135039_20170604_20200831_02_T1_G0120V02_P002.nc'], dtype=object) - interp_mask(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- light interpolation mask
- flag_meanings :
- measured interpolated
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- interpolated_value_mask
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - landice(y, x, mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- land ice mask, 0 = non-land-ice, 1 = land-ice
- flag_meanings :
- non-ice ice
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- land ice mask
- url :
- https://its-live-data.s3.amazonaws.com/autorift_parameters/v001/N46_0120m_landice.tif
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - mission_img1(mid_date)object'L' 'L' 'L' 'L' ... 'L' 'L' 'L' 'L'
- description :
- id of the mission that acquired image 1
- standard_name :
- image1_mission
array(['L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', ... 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L'], dtype=object) - mission_img2(mid_date)object'L' 'L' 'L' 'L' ... 'L' 'L' 'L' 'L'
- description :
- id of the mission that acquired image 2
- standard_name :
- image2_mission
array(['L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', ... 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L'], dtype=object) - roi_valid_percentage(mid_date)float3299.0 99.0 98.0 96.0 ... 3.9 3.2 2.0
- description :
- percentage of pixels with a valid velocity estimate determined for the intersection of the full image pair footprint and the region of interest (roi) that defines where autoRIFT tried to estimate a velocity
- standard_name :
- region_of_interest_valid_pixel_percentage
array([99. , 99. , 98. , 96. , 94.8, 94.3, 94. , 93.2, 92. , 91.5, 92. , 91.6, 91. , 91.4, 90. , 89.1, 89.3, 89.2, 88.1, 88.1, 86.9, 87. , 86.3, 86.1, 86.1, 86. , 86.4, 85.8, 85. , 84.6, 83.6, 83.7, 84. , 84.3, 82.8, 81.9, 81.6, 82. , 80.5, 80.5, 80.7, 81.1, 80.6, 79.8, 79.6, 80.1, 80.3, 78.5, 78.5, 79.1, 78.9, 77.7, 78. , 78.4, 77.3, 77.4, 76.4, 75.7, 74.7, 73.7, 73.6, 74.3, 73.6, 73.7, 73. , 73.4, 72.8, 72.6, 71.7, 71.8, 71.9, 71.8, 71.4, 70.9, 71.2, 70.7, 71.4, 69.7, 70.3, 70. , 69.6, 68.8, 69.2, 68.6, 69. , 67.7, 68.3, 68.3, 67.6, 67. , 66.5, 66.9, 67. , 66.8, 67.3, 65.6, 66. , 66.3, 66. , 65.7, 65.6, 65.4, 65.4, 64.6, 65.3, 65.4, 65. , 63.6, 63.8, 64. , 64.3, 63.5, 63.6, 63.3, 63.1, 62.5, 62.8, 62.6, 62.1, 62. , 60.7, 60.7, 61.3, 61.2, 61.1, 59.6, 60.4, 59.9, 60.1, 59.3, 58.6, 59.2, 59. , 58.6, 59.4, 58.9, 58.8, 59.2, 57.7, 58.1, 57.6, 57.6, 57.8, 58.4, 57.4, 56.8, 56.8, 56. , 56. , 55.6, 56.3, 55.8, 55.4, 55. , 55.4, 54.6, 54.3, 54.2, 54.3, 54.4, 53.4, 52.9, 53.1, 53. , 52.5, 52.7, 52.5, 51.9, 52.1, 52. , 52.1, 52.1, 52. , 51.5, 50.5, 51.4, 50.2, 49.5, 49.4, 49.3, 49.2, 48. , 48.2, 47.8, 48. , 48.2, 48. , 47. , 46.6, 46.5, 47.2, 46.7, 46.8, 47.3, 46.9, 47. , 47. , 46.9, 47.4, 46.1, 46.2, 45.8, 45.9, 44.8, 44.5, 44.6, 44.8, 44.6, 44.5, 43.5, 44. , 44.1, 44.4, 44. , 43.4, 43. , 43.3, 42.5, 42.6, 42.7, ... 22.7, 23.2, 23.4, 22.7, 22.8, 23. , 22.6, 23.4, 22.6, 22.7, 23.2, 22.8, 21.9, 22. , 22.2, 21.5, 21.6, 22.2, 22.3, 22.3, 21.5, 22.4, 22.2, 21.7, 22. , 21.7, 21.8, 22.1, 21.9, 21.5, 22.4, 22.3, 20.8, 21.2, 20.7, 20.9, 21.4, 20.8, 21. , 20.6, 20.8, 20.7, 21.2, 21. , 20.6, 20.8, 21.1, 20.5, 20.9, 20.7, 19.8, 19.5, 19.9, 19.9, 20. , 20.4, 19.9, 19.5, 20.1, 19.9, 20.3, 20.4, 20.2, 19.5, 19.6, 19.9, 20.4, 19.6, 19.3, 19.4, 18.7, 18.5, 19.4, 19.4, 18.8, 18.9, 19. , 19.1, 19. , 18.8, 18.6, 19. , 19.1, 19.1, 19.1, 18.9, 18.2, 18.1, 17.8, 17.5, 18.4, 18.4, 17.5, 18. , 18.3, 17.5, 17.7, 17.7, 17.1, 16.7, 16.6, 16.7, 17.1, 17.1, 16.5, 17. , 16.8, 17.4, 16.6, 15.5, 15.8, 16. , 15.9, 15.6, 15.7, 16.3, 16. , 15.8, 15.6, 15.7, 16.3, 16.3, 16. , 15.5, 14.7, 14.9, 15.4, 14.8, 15.2, 14.9, 14.8, 14.5, 15.3, 13.5, 13.8, 13.7, 13.6, 14.4, 14.1, 14.1, 13.6, 13.9, 13.6, 14. , 14.3, 14.2, 14.1, 14. , 12.8, 12.9, 12.9, 12.7, 12.5, 12.9, 13.1, 12.4, 11.6, 11.9, 12.4, 12.2, 11.5, 11.5, 11.7, 10.8, 10.5, 10.5, 11.2, 11.2, 11.3, 11. , 10.2, 10.3, 10. , 9.8, 9.7, 10.3, 9.7, 10.4, 9.7, 8.8, 9.3, 9.1, 8.5, 8.8, 8.8, 9.4, 8.9, 8.3, 8.4, 8.3, 8.2, 7.7, 8.1, 7.6, 8.2, 7.4, 7.2, 6.8, 7.2, 7. , 7.2, 7.4, 6.3, 5.2, 4.9, 5.2, 3.6, 3.7, 3.9, 3.2, 2. ], dtype=float32) - satellite_img1(mid_date)object'8' '8' '8' '8' ... '8' '8' '8' '8'
- description :
- id of the satellite that acquired image 1
- standard_name :
- image1_satellite
array(['8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', ... '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8'], dtype=object) - satellite_img2(mid_date)object'7' '7' '7' '7' ... '7' '7' '8' '7'
- description :
- id of the satellite that acquired image 2
- standard_name :
- image2_satellite
array(['7', '7', '7', '7', '7', '8', '7', '8', '7', '7', '7', '7', '7', '7', '7', '7', '8', '7', '7', '8', '7', '7', '8', '8', '8', '7', '8', '8', '7', '7', '7', '8', '7', '7', '8', '7', '7', '7', '7', '8', '8', '7', '8', '8', '8', '8', '7', '8', '7', '7', '8', '8', '7', '7', '7', '7', '7', '7', '7', '8', '8', '7', '7', '8', '8', '8', '8', '8', '7', '7', '8', '7', '7', '7', '8', '8', '8', '7', '7', '7', '8', '8', '8', '8', '7', '7', '7', '8', '8', '7', '7', '7', '7', '8', '8', '7', '7', '8', '7', '8', '7', '7', '8', '7', '8', '8', '8', '8', '7', '7', '8', '8', '7', '8', '8', '8', '8', '8', '7', '7', '8', '8', '7', '8', '8', '8', '8', '7', '8', '7', '7', '7', '7', '8', '8', '8', '8', '8', '7', '7', '8', '7', '8', '7', '8', '7', '8', '7', '7', '7', '8', '7', '8', '7', '8', '7', '8', '7', '8', '8', '8', '8', '8', '7', '7', '7', '8', '7', '8', '7', '7', '7', '8', '8', '8', '8', '8', '8', '7', '7', '7', '7', '8', '8', '8', '8', '7', '8', '7', '8', '7', '7', '8', '8', '7', '7', '7', '8', '7', '7', '8', '8', '8', '8', '8', '7', '7', '8', '7', '7', '8', '7', '7', '8', '7', '7', '7', '8', '7', '7', '8', '8', '7', '8', '7', '7', '8', '8', '7', '8', '7', '8', '8', '8', '8', '7', '7', '8', '8', '7', '8', '7', '7', '7', '8', '8', '8', '8', '8', '7', '7', '8', '8', '8', '8', '7', '8', '7', '8', '8', ... '7', '7', '7', '8', '8', '7', '8', '8', '7', '8', '7', '8', '7', '8', '7', '7', '8', '7', '8', '8', '7', '7', '7', '7', '7', '7', '8', '8', '7', '7', '7', '7', '7', '8', '8', '7', '8', '7', '8', '8', '7', '7', '7', '8', '8', '8', '7', '7', '8', '8', '8', '8', '8', '7', '8', '8', '7', '7', '8', '8', '8', '8', '7', '8', '8', '8', '8', '7', '7', '8', '7', '8', '7', '7', '8', '8', '8', '7', '7', '8', '8', '8', '7', '8', '7', '8', '7', '7', '7', '7', '8', '7', '7', '7', '7', '8', '8', '7', '8', '7', '7', '8', '7', '7', '8', '8', '7', '7', '7', '8', '7', '8', '7', '7', '7', '7', '7', '7', '7', '8', '7', '7', '8', '8', '7', '8', '8', '7', '7', '8', '7', '8', '8', '8', '7', '8', '7', '8', '7', '8', '7', '7', '8', '7', '7', '8', '7', '7', '8', '7', '8', '7', '7', '8', '7', '7', '7', '7', '7', '8', '7', '7', '7', '7', '7', '7', '7', '8', '7', '7', '8', '7', '8', '7', '8', '8', '7', '8', '8', '7', '7', '7', '7', '7', '7', '7', '8', '7', '8', '8', '8', '7', '8', '7', '7', '7', '8', '8', '8', '8', '7', '7', '8', '7', '7', '8', '8', '8', '8', '8', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '8', '8', '7', '8', '7', '7', '7', '8', '7', '7', '7', '8', '7', '8', '7', '7', '7', '7', '7', '7', '7', '7', '7', '8', '7'], dtype=object) - sensor_img1(mid_date)object'C' 'C' 'C' 'C' ... 'C' 'C' 'C' 'C'
- description :
- id of the sensor that acquired image 1
- standard_name :
- image1_sensor
array(['C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', ... 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C'], dtype=object) - sensor_img2(mid_date)object'E' 'E' 'E' 'E' ... 'E' 'E' 'C' 'E'
- description :
- id of the sensor that acquired image 2
- standard_name :
- image2_sensor
array(['E', 'E', 'E', 'E', 'E', 'C', 'E', 'C', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'C', 'E', 'E', 'C', 'E', 'E', 'C', 'C', 'C', 'E', 'C', 'C', 'E', 'E', 'E', 'C', 'E', 'E', 'C', 'E', 'E', 'E', 'E', 'C', 'C', 'E', 'C', 'C', 'C', 'C', 'E', 'C', 'E', 'E', 'C', 'C', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'C', 'C', 'E', 'E', 'C', 'C', 'C', 'C', 'C', 'E', 'E', 'C', 'E', 'E', 'E', 'C', 'C', 'C', 'E', 'E', 'E', 'C', 'C', 'C', 'C', 'E', 'E', 'E', 'C', 'C', 'E', 'E', 'E', 'E', 'C', 'C', 'E', 'E', 'C', 'E', 'C', 'E', 'E', 'C', 'E', 'C', 'C', 'C', 'C', 'E', 'E', 'C', 'C', 'E', 'C', 'C', 'C', 'C', 'C', 'E', 'E', 'C', 'C', 'E', 'C', 'C', 'C', 'C', 'E', 'C', 'E', 'E', 'E', 'E', 'C', 'C', 'C', 'C', 'C', 'E', 'E', 'C', 'E', 'C', 'E', 'C', 'E', 'C', 'E', 'E', 'E', 'C', 'E', 'C', 'E', 'C', 'E', 'C', 'E', 'C', 'C', 'C', 'C', 'C', 'E', 'E', 'E', 'C', 'E', 'C', 'E', 'E', 'E', 'C', 'C', 'C', 'C', 'C', 'C', 'E', 'E', 'E', 'E', 'C', 'C', 'C', 'C', 'E', 'C', 'E', 'C', 'E', 'E', 'C', 'C', 'E', 'E', 'E', 'C', 'E', 'E', 'C', 'C', 'C', 'C', 'C', 'E', 'E', 'C', 'E', 'E', 'C', 'E', 'E', 'C', 'E', 'E', 'E', 'C', 'E', 'E', 'C', 'C', 'E', 'C', 'E', 'E', 'C', 'C', 'E', 'C', 'E', 'C', 'C', 'C', 'C', 'E', 'E', 'C', 'C', 'E', 'C', 'E', 'E', 'E', 'C', 'C', 'C', 'C', 'C', 'E', 'E', 'C', 'C', 'C', 'C', 'E', 'C', 'E', 'C', 'C', ... 'E', 'E', 'E', 'C', 'C', 'E', 'C', 'C', 'E', 'C', 'E', 'C', 'E', 'C', 'E', 'E', 'C', 'E', 'C', 'C', 'E', 'E', 'E', 'E', 'E', 'E', 'C', 'C', 'E', 'E', 'E', 'E', 'E', 'C', 'C', 'E', 'C', 'E', 'C', 'C', 'E', 'E', 'E', 'C', 'C', 'C', 'E', 'E', 'C', 'C', 'C', 'C', 'C', 'E', 'C', 'C', 'E', 'E', 'C', 'C', 'C', 'C', 'E', 'C', 'C', 'C', 'C', 'E', 'E', 'C', 'E', 'C', 'E', 'E', 'C', 'C', 'C', 'E', 'E', 'C', 'C', 'C', 'E', 'C', 'E', 'C', 'E', 'E', 'E', 'E', 'C', 'E', 'E', 'E', 'E', 'C', 'C', 'E', 'C', 'E', 'E', 'C', 'E', 'E', 'C', 'C', 'E', 'E', 'E', 'C', 'E', 'C', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'C', 'E', 'E', 'C', 'C', 'E', 'C', 'C', 'E', 'E', 'C', 'E', 'C', 'C', 'C', 'E', 'C', 'E', 'C', 'E', 'C', 'E', 'E', 'C', 'E', 'E', 'C', 'E', 'E', 'C', 'E', 'C', 'E', 'E', 'C', 'E', 'E', 'E', 'E', 'E', 'C', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'C', 'E', 'E', 'C', 'E', 'C', 'E', 'C', 'C', 'E', 'C', 'C', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'C', 'E', 'C', 'C', 'C', 'E', 'C', 'E', 'E', 'E', 'C', 'C', 'C', 'C', 'E', 'E', 'C', 'E', 'E', 'C', 'C', 'C', 'C', 'C', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'C', 'C', 'E', 'C', 'E', 'E', 'E', 'C', 'E', 'E', 'E', 'C', 'E', 'C', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'C', 'E'], dtype=object) - stable_count_slow(mid_date)float646.304e+04 6.037e+04 ... 3.688e+04
- description :
- number of valid pixels over slowest 25% of ice
- standard_name :
- stable_count_slow
- units :
- count
array([63035., 60373., 12343., 43082., 26491., 41111., 5234., 24156., 47472., 13668., 22255., 49070., 11254., 35948., 60149., 5853., 1344., 61020., 62075., 38755., 20004., 424., 9003., 41705., 61020., 64087., 2841., 7868., 57652., 59507., 34883., 24203., 33517., 33987., 16150., 28827., 37578., 44729., 27785., 32064., 46694., 34529., 21574., 25079., 9514., 8015., 8031., 59955., 23049., 31137., 51235., 28297., 27069., 34225., 13281., 56023., 23842., 28060., 3054., 1900., 58830., 53653., 7165., 18550., 837., 13570., 60550., 35035., 42190., 45460., 59604., 30918., 51360., 11801., 16620., 36272., 27701., 13951., 16316., 59570., 58244., 35443., 64503., 27244., 17355., 1033., 59833., 14269., 58196., 34335., 31096., 17376., 41960., 23150., 65147., 7167., 15968., 51774., 47622., 44522., 65002., 7610., 31988., 45997., 37338., 43251., 33428., 6550., 32017., 10284., 17732., 331., 28831., 63337., 40266., 7611., 59878., 62832., 6638., 34323., 65115., 9267., 63444., 29687., 24507., 24201., 63105., 29168., 28008., 206., 32203., 30702., 58734., 20705., 11115., 59811., 41530., 37826., 52639., 63734., 45659., 16863., 13621., 30455., 499., 13107., 7792., 7019., 47502., 53152., 59775., 37539., 40859., 54742., 56060., 21825., 28260., 3769., 13957., 62151., ... 10672., 22941., 25814., 31612., 17666., 24056., 34373., 26102., 28616., 28178., 45737., 26513., 33471., 56429., 17951., 21749., 13671., 58606., 4961., 20377., 23440., 36254., 12754., 36856., 11180., 17468., 14532., 64600., 6912., 14823., 15753., 60817., 91., 60269., 39126., 35025., 55769., 8743., 29328., 50861., 1140., 21479., 55823., 18826., 45835., 16928., 35408., 18706., 37431., 22255., 39943., 7006., 30998., 34389., 34800., 37857., 16363., 3370., 10762., 24777., 17802., 22717., 49088., 25460., 23318., 52591., 24147., 34095., 31210., 45471., 10050., 46735., 3922., 8560., 2283., 7899., 6590., 4402., 1580., 36763., 48007., 53991., 25463., 45877., 31006., 49171., 33808., 14079., 50711., 16674., 16505., 42561., 62449., 57698., 52210., 32016., 38178., 38618., 4528., 29653., 5548., 9857., 42546., 4101., 47325., 8395., 24288., 6025., 36064., 48022., 20782., 11596., 59693., 6552., 9688., 8746., 3430., 46778., 20340., 54888., 4175., 42428., 48928., 44147., 55754., 46092., 29312., 35464., 23887., 22110., 29426., 25222., 36564., 53833., 43041., 18602., 43977., 12535., 8458., 5600., 15194., 16590., 3313., 54030., 10567., 57964., 16440., 62997., 2114., 46046., 27250., 22745., 27624., 65414., 720., 5714., 741., 36880.]) - stable_count_stationary(mid_date)float644.997e+04 4.807e+04 ... 3.666e+04
- description :
- number of valid pixels over stationary or slow-flowing surfaces
- standard_name :
- stable_count_stationary
- units :
- count
array([49966., 48073., 303., 33034., 15317., 29397., 57881., 11745., 37249., 3328., 11144., 38786., 65160., 25475., 47735., 61322., 55699., 50706., 50666., 26524., 11672., 54765., 65361., 30703., 48711., 53048., 59176., 62314., 47070., 48888., 24233., 13263., 22702., 22907., 4018., 20801., 26847., 33581., 17051., 20313., 34898., 24311., 11918., 14255., 854., 63893., 664., 48469., 14334., 22758., 40298., 17217., 19186., 24607., 3325., 45674., 13622., 18203., 57587., 57691., 49837., 43783., 1201., 8257., 55254., 3393., 50063., 23712., 32251., 35705., 48520., 20837., 44025., 2523., 6459., 25714., 16999., 7926., 9028., 53551., 48451., 25075., 54163., 18290., 9795., 57504., 50618., 5699., 47462., 25253., 21756., 7926., 32465., 13509., 57164., 65487., 7084., 42602., 38503., 35417., 54595., 818., 23467., 37409., 29776., 35448., 23144., 64276., 21197., 1207., 8606., 56376., 21813., 56012., 31389., 65294., 52383., 53189., 755., 27655., 58126., 1404., 54542., 23774., 15492., 16333., 55708., 23157., 21400., 56958., 24653., 22206., 50416., 15050., 974., 52083., 34016., 30198., 44341., 53557., 38135., 9866., 6522., 24581., 59787., 6340., 1160., 65195., 39592., 46419., 51581., 29483., 33011., 46589., 50920., 16480., 17286., 62451., 5505., 56517., ... 9004., 21593., 23905., 30383., 16942., 22941., 30534., 20923., 25205., 24625., 44103., 24357., 31437., 53151., 14934., 16799., 12184., 56748., 4249., 19511., 21640., 33733., 11876., 33225., 9185., 16593., 11519., 63314., 6104., 13893., 14533., 57261., 63018., 56920., 38064., 32711., 55129., 7059., 27468., 49458., 65282., 17593., 55130., 15438., 44889., 15777., 32578., 17236., 36879., 20804., 38726., 5770., 30066., 31533., 33904., 35181., 14161., 873., 10199., 24148., 14633., 20193., 45850., 23312., 22448., 51561., 23655., 33411., 30384., 44593., 7192., 45351., 2744., 6638., 65203., 6667., 3872., 2381., 105., 33177., 46110., 53471., 23036., 45115., 27790., 48108., 31610., 13088., 49025., 14576., 15454., 40977., 61909., 55746., 50068., 31038., 37007., 35190., 2323., 28814., 1635., 6825., 41348., 3611., 45925., 6795., 22592., 4678., 34536., 46728., 18440., 9141., 59213., 5137., 8486., 7226., 2542., 45022., 18757., 53618., 2411., 39766., 47998., 43279., 54898., 45476., 29048., 33988., 22693., 21080., 28782., 24120., 35082., 52449., 41838., 18095., 42759., 12144., 7826., 4920., 13393., 15234., 2163., 53008., 8496., 56534., 15672., 62238., 608., 45667., 26900., 22747., 27302., 64980., 65202., 5504., 64491., 36655.]) - stable_shift_flag(mid_date)float641.0 1.0 1.0 1.0 ... 1.0 1.0 1.0 1.0
- description :
- flag for applying velocity bias correction: 0 = no correction; 1 = correction from overlapping stable surface mask (stationary or slow-flowing surfaces with velocity < 15 m/yr)(top priority); 2 = correction from slowest 25% of overlapping velocities (second priority)
- standard_name :
- stable_shift_flag
array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.]) - v(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity magnitude
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_velocity
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - v_error(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity magnitude error
- grid_mapping :
- mapping
- standard_name :
- velocity_error
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - va(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity in radar azimuth direction
- grid_mapping :
- mapping
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - va_error(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- error for velocity in radar azimuth direction
- standard_name :
- va_error
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - va_error_modeled(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- va_error_modeled
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - va_error_slow(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- va_error_slow
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - va_error_stationary(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- va_error_stationary
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - va_stable_shift(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- applied va shift calibrated using pixels over stable or slow surfaces
- standard_name :
- va_stable_shift
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - va_stable_shift_slow(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- va shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- va_stable_shift_slow
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - va_stable_shift_stationary(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- va shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- va_stable_shift_stationary
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vr(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity in radar range direction
- grid_mapping :
- mapping
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - vr_error(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- error for velocity in radar range direction
- standard_name :
- vr_error
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vr_error_modeled(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vr_error_modeled
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vr_error_slow(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vr_error_slow
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vr_error_stationary(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vr_error_stationary
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vr_stable_shift(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- applied vr shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vr_stable_shift
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vr_stable_shift_slow(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- vr shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vr_stable_shift_slow
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vr_stable_shift_stationary(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- vr shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vr_stable_shift_stationary
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vx(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity component in x direction
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_x_velocity
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - vx_error(mid_date)float32321.3 61.7 119.5 ... 5.5 11.3 51.0
- description :
- best estimate of x_velocity error: vx_error is populated according to the approach used for the velocity bias correction as indicated in "stable_shift_flag"
- standard_name :
- vx_error
- units :
- meter/year
array([321.3, 61.7, 119.5, 8.6, 7.1, 1.5, 322.9, 2. , 337.7, 46.7, 7.8, 6.5, 50.6, 8.8, 363.2, 8.1, 2.5, 8. , 120.2, 1.9, 10.7, 99.5, 3. , 10.2, 15. , 107.6, 3.3, 2.5, 8. , 8. , 6.8, 2.3, 377.4, 7.5, 2.3, 5.7, 51.7, 59. , 8.5, 2.5, 2.2, 6.6, 2.5, 1.9, 3.2, 2.2, 7. , 2.3, 7. , 10. , 4. , 2.5, 26.1, 7.4, 7.5, 7.7, 76.3, 10.7, 374.1, 2.2, 6.2, 78.1, 12.8, 3. , 2.6, 1.9, 2.6, 18.1, 53.8, 6.2, 2. , 10. , 6.4, 8.9, 11. , 1.8, 9.9, 12.1, 21.2, 148.5, 2.4, 2.5, 3.1, 7.3, 357.7, 5.4, 7.4, 3.4, 11.9, 37.2, 34.5, 9.5, 365.1, 33.6, 2.2, 39.7, 72.9, 2.3, 8.4, 14.3, 8.4, 10. , 2.3, 10.9, 2.3, 2.9, 16.4, 1.8, 68.9, 7.9, 4. , 11.5, 117.2, 2. , 13.2, 15.4, 1.8, 2. , 8. , 136.6, 42.9, 41.5, 16.1, 8.5, 37. , 2.5, 2.4, 76.6, 1.7, 11.4, 7. , 29.5, 110.7, 2.3, 10.6, 11.4, 2.2, 11.4, 7. , 149.5, 2.4, 8.9, 3.1, 33.2, 2.3, 25.8, 16.1, 7. , 52.1, 4.3, 8.2, 330.7, 24. , 450.8, 18. , 10.1, 41.7, 61.2, 3.7, 10.6, 2.4, 11.6, 2.3, 20.8, 9.1, 110.7, 2.4, 7.5, 2.1, 10.6, 5.9, 34. , 2.2, 4.3, 1.8, 2.4, 2.3, 2.5, 46.4, 7.4, ... 10.4, 4.9, 9.1, 7.2, 31.4, 6.3, 6.3, 19.6, 16.7, 3.9, 3.3, 1.5, 22.2, 1.9, 7.1, 1.9, 9. , 10.4, 15.8, 10. , 4.9, 9.4, 50. , 63.4, 9.5, 2.9, 4.6, 5.1, 6.7, 11. , 5.9, 2.9, 15.2, 272. , 3.6, 13.4, 19.6, 7.6, 14. , 9.6, 6.5, 7.5, 12.5, 40.7, 10. , 29.8, 43.2, 6.4, 71.6, 2.7, 17.8, 9.6, 12.7, 1.6, 19.9, 8. , 10.3, 15.7, 5.1, 10.4, 29.5, 6. , 2.8, 3.9, 14.7, 2.2, 5.2, 2.1, 19.8, 2.7, 19. , 26. , 7. , 10.7, 13.4, 4.4, 23.8, 19.6, 2.4, 10.5, 7.9, 43. , 11.8, 6.2, 33.4, 16.2, 10.3, 7. , 11.4, 3.7, 8.3, 10.2, 4.1, 44.3, 101. , 6.1, 56.2, 4. , 8.4, 7.1, 8.5, 9.8, 2.4, 10.8, 2.4, 4.4, 13.7, 2. , 4.9, 7.3, 16.9, 4.9, 6.6, 31.3, 31. , 152.6, 5.2, 39.9, 5.1, 2.4, 6.4, 14.8, 3. , 11.9, 5.9, 22.1, 4.5, 3.9, 2. , 7.2, 23.2, 11.1, 3.2, 13.2, 9.7, 5.1, 2.2, 8.5, 8.5, 2.4, 13. , 12.7, 162.5, 9.3, 10.7, 3.5, 23.3, 7.6, 7.1, 5.8, 15.9, 5.9, 2.1, 14.5, 2.8, 66.5, 29.7, 5.8, 3.7, 15.4, 7.1, 36. , 1.9, 26.1, 6.9, 6.2, 3.9, 51.1, 3.8, 21.7, 16.2, 35.9, 35.3, 5.5, 11.3, 51. ], dtype=float32) - vx_error_modeled(mid_date)float321.163e+03 232.7 ... 97.0 166.2
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vx_error_modeled
- units :
- meter/year
array([1163.2, 232.7, 387.9, 28.4, 27.1, 20.8, 1163.2, 26.4, 1163.2, 166.2, 24.8, 24.8, 166.2, 28.4, 1163.8, 25.9, 29.1, 27.1, 387.8, 25.3, 33.2, 387.8, 30.6, 116.3, 193.9, 387.9, 34.2, 18.8, 24.8, 25.9, 22. , 27.7, 1163.9, 23.7, 17.6, 22. , 166.2, 232.7, 29.8, 22.4, 23.3, 19.7, 20.8, 21.5, 32.3, 24.2, 22.8, 25.3, 23.7, 31.4, 38.8, 22.4, 89.5, 23.7, 22.8, 27.1, 232.7, 29.8, 1164. , 27.7, 36.4, 232.7, 31.4, 29.1, 29.1, 22.4, 21.5, 145.4, 166.2, 18.5, 17.6, 28.4, 21.2, 33.2, 145.4, 24.2, 97. , 29.8, 68.4, 387.8, 22.4, 26.4, 26.4, 41.6, 1163.9, 17.4, 22. , 32.3, 97. , 129.3, 105.8, 31.4, 1163.3, 581.7, 18.8, 129.3, 232.7, 20.8, 25.9, 193.9, 22.8, 23.7, 18.2, 35.3, 23.3, 21.5, 193.9, 24.2, 232.7, 24.8, 36.4, 64.6, 387.8, 21.5, 116.3, 116.3, 22.4, 25.3, 24.8, 387.9, 581.7, 581.7, 55.4, 97. , 581.7, 30.6, 21.5, 232.7, 23.3, 37.5, 23.7, 105.8, 387.8, 18.2, 145.4, 145.4, 23.3, 116.3, 20.4, 387.8, 29.1, 24.8, 27.7, 105.8, 20.1, 77.6, 193.9, 22.8, 166.2, 25.9, 52.9, 1163.2, 290.9, 1163.2, 145.4, 28.4, 581.7, 166.2, 30.6, 97. , ... 46.5, 22. , 38.8, 31.4, 129.3, 166.2, 27.1, 26.4, 38.8, 18.5, 72.7, 35.3, 17.4, 27.7, 43.1, 1163.2, 34.2, 145.4, 50.6, 20.4, 43.1, 83.1, 19.1, 64.6, 29.8, 89.5, 22.8, 68.4, 105.8, 19.7, 166.2, 17.1, 61.2, 35.3, 116.3, 25.3, 55.4, 64.6, 72.7, 40.1, 17.4, 97. , 61.2, 52.9, 20.1, 38.8, 37.5, 17.1, 17.9, 21.5, 61.2, 19.4, 68.4, 89.5, 64.6, 40.1, 46.5, 41.6, 77.6, 46.5, 29.1, 25.9, 83.1, 105.8, 33.2, 48.5, 68.4, 50.6, 37.5, 20.4, 61.2, 30.6, 29.8, 50.6, 19.7, 166.2, 232.7, 18.5, 129.3, 34.2, 19.1, 17.4, 83.1, 35.3, 19.4, 24.8, 24.2, 41.6, 35.3, 22.4, 44.7, 24.8, 46.5, 17.9, 20.4, 77.6, 77.6, 387.8, 48.5, 89.5, 38.8, 22.4, 64.6, 50.6, 27.7, 31.4, 17.4, 68.4, 41.6, 30.6, 17.6, 48.5, 55.4, 33.2, 32.3, 46.5, 21.2, 38.8, 18.8, 72.7, 83.1, 30.6, 50.6, 37.5, 387.8, 19.7, 40.1, 19.1, 77.6, 31.4, 22.8, 35.3, 46.5, 52.9, 17.1, 55.4, 17.6, 232.7, 68.4, 25.9, 34.2, 37.5, 28.4, 166.2, 17.6, 89.5, 58.2, 21.2, 20.4, 129.3, 22.8, 55.4, 40.1, 105.8, 105.8, 18.5, 97. , 166.2], dtype=float32) - vx_error_slow(mid_date)float32321.0 61.6 119.3 ... 5.5 11.2 50.9
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vx_error_slow
- units :
- meter/year
array([321. , 61.6, 119.3, 8.5, 7.1, 1.5, 322.2, 2. , 337.5, 46.6, 7.8, 6.5, 50.5, 8.8, 363. , 8.1, 2.5, 8. , 120. , 1.9, 10.7, 99.4, 3. , 10.2, 15. , 107.5, 3.3, 2.5, 8. , 8. , 6.8, 2.3, 376.7, 7.5, 2.3, 5.7, 51.6, 58.9, 8.5, 2.5, 2.2, 6.6, 2.5, 1.9, 3.2, 2.2, 7. , 2.3, 7. , 10. , 4. , 2.5, 26.1, 7.4, 7.5, 7.7, 76.1, 10.7, 373.2, 2.2, 6.2, 78. , 12.8, 3. , 2.6, 1.9, 2.6, 18.1, 53.7, 6.2, 2. , 10. , 6.4, 8.9, 11. , 1.8, 9.9, 12.1, 21.2, 148.4, 2.4, 2.5, 3.1, 7.3, 357.3, 5.4, 7.4, 3.4, 11.9, 37.2, 34.5, 9.5, 364.7, 33.6, 2.2, 39.6, 72.8, 2.3, 8.4, 14.2, 8.4, 10. , 2.3, 10.9, 2.3, 2.9, 16.4, 1.8, 68.7, 7.9, 4. , 11.5, 117.1, 2. , 13.1, 15.4, 1.8, 2. , 8. , 136.4, 42.9, 41.5, 16.1, 8.5, 37. , 2.5, 2.5, 76.5, 1.7, 11.4, 7. , 29.4, 110.5, 2.3, 10.6, 11.4, 2.2, 11.4, 7. , 149.1, 2.4, 8.8, 3.1, 33.1, 2.3, 25.8, 16.1, 7. , 52.1, 4.3, 8.2, 329.9, 24. , 449.9, 18. , 10.1, 41.7, 61.1, 3.7, 10.6, 2.4, 11.6, 2.3, 20.8, 9.1, 110.5, 2.4, 7.5, 2.1, 10.6, 5.9, 34. , 2.2, 4.3, 1.8, 2.4, 2.3, 2.5, 46.4, 7.4, ... 10.4, 4.9, 9.1, 7.2, 31.4, 6.3, 6.3, 19.6, 16.6, 3.9, 3.3, 1.5, 22.2, 1.9, 7.1, 1.9, 9. , 10.4, 15.8, 10. , 4.9, 9.4, 49.9, 63.3, 9.5, 2.9, 4.6, 5.1, 6.7, 11. , 5.8, 2.9, 15.2, 271.7, 3.6, 13.4, 19.6, 7.6, 14. , 9.6, 6.5, 7.5, 12.5, 40.7, 10. , 29.8, 43.2, 6.4, 71.6, 2.7, 17.8, 9.6, 12.7, 1.6, 19.9, 8. , 10.3, 15.6, 5.1, 10.4, 29.5, 6. , 2.8, 3.9, 14.6, 2.2, 5.2, 2.1, 19.8, 2.7, 19. , 26. , 7. , 10.7, 13.4, 4.4, 23.8, 19.6, 2.4, 10.5, 7.9, 43. , 11.8, 6.2, 33.4, 16.2, 10.3, 7. , 11.4, 3.7, 8.3, 10.1, 4.1, 44.3, 100.6, 6.1, 56.2, 3.9, 8.4, 7.1, 8.5, 9.8, 2.4, 10.8, 2.4, 4.4, 13.7, 2. , 4.9, 7.3, 16.9, 4.9, 6.6, 31.4, 31. , 151.7, 5.2, 39.9, 5.1, 2.4, 6.4, 14.8, 3. , 11.9, 5.9, 22.1, 4.5, 3.9, 2. , 7.2, 23.2, 11.1, 3.2, 13.2, 9.7, 5.1, 2.2, 8.5, 8.5, 2.4, 13.1, 12.7, 162.4, 9.3, 10.6, 3.5, 23.3, 7.6, 7.1, 5.8, 15.8, 5.9, 2.1, 14.4, 2.8, 66.5, 29.6, 5.7, 3.7, 15.3, 7.1, 35.9, 1.9, 26.1, 6.9, 6.2, 3.9, 51.2, 3.8, 21.7, 16.3, 36.4, 35.2, 5.5, 11.2, 50.9], dtype=float32) - vx_error_stationary(mid_date)float32321.3 61.7 119.5 ... 5.5 11.3 51.0
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 meter/year identified from an external mask
- standard_name :
- vx_error_stationary
- units :
- meter/year
array([321.3, 61.7, 119.5, 8.6, 7.1, 1.5, 322.9, 2. , 337.7, 46.7, 7.8, 6.5, 50.6, 8.8, 363.2, 8.1, 2.5, 8. , 120.2, 1.9, 10.7, 99.5, 3. , 10.2, 15. , 107.6, 3.3, 2.5, 8. , 8. , 6.8, 2.3, 377.4, 7.5, 2.3, 5.7, 51.7, 59. , 8.5, 2.5, 2.2, 6.6, 2.5, 1.9, 3.2, 2.2, 7. , 2.3, 7. , 10. , 4. , 2.5, 26.1, 7.4, 7.5, 7.7, 76.3, 10.7, 374.1, 2.2, 6.2, 78.1, 12.8, 3. , 2.6, 1.9, 2.6, 18.1, 53.8, 6.2, 2. , 10. , 6.4, 8.9, 11. , 1.8, 9.9, 12.1, 21.2, 148.5, 2.4, 2.5, 3.1, 7.3, 357.7, 5.4, 7.4, 3.4, 11.9, 37.2, 34.5, 9.5, 365.1, 33.6, 2.2, 39.7, 72.9, 2.3, 8.4, 14.3, 8.4, 10. , 2.3, 10.9, 2.3, 2.9, 16.4, 1.8, 68.9, 7.9, 4. , 11.5, 117.2, 2. , 13.2, 15.4, 1.8, 2. , 8. , 136.6, 42.9, 41.5, 16.1, 8.5, 37. , 2.5, 2.4, 76.6, 1.7, 11.4, 7. , 29.5, 110.7, 2.3, 10.6, 11.4, 2.2, 11.4, 7. , 149.5, 2.4, 8.9, 3.1, 33.2, 2.3, 25.8, 16.1, 7. , 52.1, 4.3, 8.2, 330.7, 24. , 450.8, 18. , 10.1, 41.7, 61.2, 3.7, 10.6, 2.4, 11.6, 2.3, 20.8, 9.1, 110.7, 2.4, 7.5, 2.1, 10.6, 5.9, 34. , 2.2, 4.3, 1.8, 2.4, 2.3, 2.5, 46.4, 7.4, ... 10.4, 4.9, 9.1, 7.2, 31.4, 6.3, 6.3, 19.6, 16.7, 3.9, 3.3, 1.5, 22.2, 1.9, 7.1, 1.9, 9. , 10.4, 15.8, 10. , 4.9, 9.4, 50. , 63.4, 9.5, 2.9, 4.6, 5.1, 6.7, 11. , 5.9, 2.9, 15.2, 272. , 3.6, 13.4, 19.6, 7.6, 14. , 9.6, 6.5, 7.5, 12.5, 40.7, 10. , 29.8, 43.2, 6.4, 71.6, 2.7, 17.8, 9.6, 12.7, 1.6, 19.9, 8. , 10.3, 15.7, 5.1, 10.4, 29.5, 6. , 2.8, 3.9, 14.7, 2.2, 5.2, 2.1, 19.8, 2.7, 19. , 26. , 7. , 10.7, 13.4, 4.4, 23.8, 19.6, 2.4, 10.5, 7.9, 43. , 11.8, 6.2, 33.4, 16.2, 10.3, 7. , 11.4, 3.7, 8.3, 10.2, 4.1, 44.3, 101. , 6.1, 56.2, 4. , 8.4, 7.1, 8.5, 9.8, 2.4, 10.8, 2.4, 4.4, 13.7, 2. , 4.9, 7.3, 16.9, 4.9, 6.6, 31.3, 31. , 152.6, 5.2, 39.9, 5.1, 2.4, 6.4, 14.8, 3. , 11.9, 5.9, 22.1, 4.5, 3.9, 2. , 7.2, 23.2, 11.1, 3.2, 13.2, 9.7, 5.1, 2.2, 8.5, 8.5, 2.4, 13. , 12.7, 162.5, 9.3, 10.7, 3.5, 23.3, 7.6, 7.1, 5.8, 15.9, 5.9, 2.1, 14.5, 2.8, 66.5, 29.7, 5.8, 3.7, 15.4, 7.1, 36. , 1.9, 26.1, 6.9, 6.2, 3.9, 51.1, 3.8, 21.7, 16.2, 35.9, 35.3, 5.5, 11.3, 51. ], dtype=float32) - vx_stable_shift(mid_date)float32-42.8 8.6 0.0 -2.1 ... 0.3 3.6 30.8
- description :
- applied vx shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vx_stable_shift
- units :
- meter/year
array([-4.280e+01, 8.600e+00, 0.000e+00, -2.100e+00, 1.000e+00, 8.000e-01, -8.550e+01, 0.000e+00, 0.000e+00, -1.220e+01, 2.100e+00, 9.000e-01, 1.220e+01, -7.000e-01, -4.280e+01, 0.000e+00, 0.000e+00, -2.200e+00, 3.970e+01, 0.000e+00, 0.000e+00, 2.640e+01, 0.000e+00, 0.000e+00, 0.000e+00, 1.430e+01, 0.000e+00, 0.000e+00, 0.000e+00, 1.300e+00, -1.400e+00, -6.000e-01, -4.280e+01, 1.500e+00, 0.000e+00, 6.000e-01, 1.830e+01, 8.600e+00, -1.100e+00, -8.000e-01, 0.000e+00, 1.400e+00, 0.000e+00, 8.000e-01, -1.200e+00, 0.000e+00, -8.000e-01, 0.000e+00, -9.000e-01, -8.000e-01, 1.400e+00, -8.000e-01, 5.300e+00, 1.700e+00, -2.000e-01, -4.000e-01, 1.220e+01, 9.000e-01, 4.900e+00, 2.000e-01, 1.300e+00, 7.300e+00, -4.000e+00, 0.000e+00, 1.100e+00, 8.000e-01, -1.300e+00, -5.300e+00, -2.000e-01, 0.000e+00, 0.000e+00, 5.000e-01, 1.300e+00, 2.900e+00, 0.000e+00, 0.000e+00, 0.000e+00, -4.300e+00, -1.200e+00, -4.930e+01, 0.000e+00, 0.000e+00, 6.000e-01, 1.500e+00, 0.000e+00, -5.000e-01, -8.000e-01, 2.100e+00, -3.600e+00, 1.170e+01, 0.000e+00, 3.500e+00, 4.280e+01, 0.000e+00, 0.000e+00, -9.500e+00, 8.600e+00, 0.000e+00, 4.000e-01, 7.100e+00, ... 1.200e+00, -3.100e+00, 7.700e+00, -1.000e-01, -8.000e-01, 1.680e+01, 6.000e-01, 9.600e+00, 8.000e-01, -5.300e+00, -1.100e+00, 4.400e+00, -3.400e+00, -1.600e+00, 2.450e+01, 9.200e+00, 1.000e+00, 1.430e+01, 1.300e+00, 8.000e-01, 3.800e+00, -2.000e-01, 2.600e+00, 0.000e+00, 5.300e+00, 9.000e-01, 1.500e+00, 6.500e+00, 0.000e+00, 2.600e+00, 0.000e+00, 7.600e+00, 1.400e+00, 1.100e+00, 1.700e+00, 3.200e+00, 9.600e+00, 0.000e+00, 1.610e+01, -1.400e+00, 1.300e+00, -1.300e+00, 9.200e+00, 0.000e+00, -8.100e+00, 4.100e+00, 1.200e+01, 0.000e+00, 1.900e+00, -4.000e-01, -1.000e-01, 1.400e+01, 2.100e+00, 1.200e+00, 2.000e-01, 3.100e+00, -1.400e+00, 0.000e+00, 2.700e+00, 8.000e-01, 1.000e+00, 9.800e+00, 8.300e+00, 2.850e+01, 7.000e-01, 5.000e+00, -3.000e-01, 6.500e+00, 8.100e+00, 1.400e+00, -1.200e+00, 6.200e+00, -1.900e+00, 6.000e-01, 1.020e+01, 7.000e-01, 8.190e+01, 7.200e+00, 0.000e+00, -1.200e+00, 5.300e+00, -7.000e-01, 3.400e+00, 2.000e-01, -1.800e+00, 1.800e+00, 0.000e+00, -1.200e+00, 6.010e+01, -1.500e+00, 1.590e+01, 1.550e+01, 5.940e+01, -6.300e+00, 3.000e-01, 3.600e+00, 3.080e+01], dtype=float32) - vx_stable_shift_slow(mid_date)float32-42.8 8.6 0.0 -2.1 ... 0.3 3.6 30.5
- description :
- vx shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vx_stable_shift_slow
- units :
- meter/year
array([-4.280e+01, 8.600e+00, 0.000e+00, -2.100e+00, 1.000e+00, 8.000e-01, -8.550e+01, 0.000e+00, 0.000e+00, -1.220e+01, 2.100e+00, 9.000e-01, 1.220e+01, -7.000e-01, -4.280e+01, 0.000e+00, 0.000e+00, -2.200e+00, 4.030e+01, 0.000e+00, 0.000e+00, 2.700e+01, 0.000e+00, 0.000e+00, 0.000e+00, 1.430e+01, 0.000e+00, 0.000e+00, 0.000e+00, 1.300e+00, -1.400e+00, -7.000e-01, -4.280e+01, 1.500e+00, 0.000e+00, 6.000e-01, 1.830e+01, 8.600e+00, -1.100e+00, -8.000e-01, 0.000e+00, 1.400e+00, 0.000e+00, 8.000e-01, -1.200e+00, 0.000e+00, -8.000e-01, 0.000e+00, -9.000e-01, -7.000e-01, 1.400e+00, -8.000e-01, 5.300e+00, 1.700e+00, -1.000e-01, -4.000e-01, 1.230e+01, 9.000e-01, 6.400e+00, 2.000e-01, 1.300e+00, 7.500e+00, -4.000e+00, 0.000e+00, 1.100e+00, 8.000e-01, -1.300e+00, -5.300e+00, -1.000e-01, 0.000e+00, 0.000e+00, 5.000e-01, 1.300e+00, 2.900e+00, 0.000e+00, 0.000e+00, 0.000e+00, -4.200e+00, -1.200e+00, -4.900e+01, 0.000e+00, 0.000e+00, 6.000e-01, 1.500e+00, 0.000e+00, -5.000e-01, -8.000e-01, 2.100e+00, -3.600e+00, 1.190e+01, 0.000e+00, 3.500e+00, 4.280e+01, 0.000e+00, 0.000e+00, -9.500e+00, 8.600e+00, 0.000e+00, 5.000e-01, 7.100e+00, ... 1.200e+00, -3.100e+00, 7.300e+00, -2.000e-01, -8.000e-01, 1.680e+01, 6.000e-01, 9.700e+00, 8.000e-01, -5.300e+00, -1.100e+00, 4.400e+00, -3.300e+00, -1.600e+00, 2.440e+01, 8.600e+00, 1.000e+00, 1.400e+01, 1.300e+00, 7.000e-01, 3.800e+00, -1.000e-01, 2.600e+00, 0.000e+00, 5.300e+00, 9.000e-01, 1.500e+00, 6.500e+00, 0.000e+00, 2.500e+00, 0.000e+00, 7.600e+00, 1.400e+00, 1.100e+00, 1.700e+00, 3.100e+00, 1.020e+01, 0.000e+00, 1.580e+01, -1.400e+00, 1.300e+00, -1.400e+00, 9.200e+00, 0.000e+00, -8.100e+00, 4.000e+00, 1.200e+01, 0.000e+00, 1.900e+00, -4.000e-01, 0.000e+00, 1.410e+01, 2.100e+00, 1.200e+00, 1.000e-01, 3.100e+00, -1.400e+00, 0.000e+00, 2.700e+00, 7.000e-01, 9.000e-01, 9.800e+00, 8.300e+00, 2.850e+01, 7.000e-01, 5.100e+00, -3.000e-01, 6.400e+00, 8.100e+00, 1.400e+00, -1.200e+00, 6.100e+00, -1.900e+00, 6.000e-01, 1.020e+01, 7.000e-01, 8.180e+01, 7.000e+00, 0.000e+00, -1.200e+00, 5.100e+00, -7.000e-01, 3.500e+00, 3.000e-01, -1.800e+00, 1.900e+00, 0.000e+00, -1.200e+00, 6.000e+01, -1.500e+00, 1.590e+01, 1.540e+01, 5.920e+01, -6.300e+00, 3.000e-01, 3.600e+00, 3.050e+01], dtype=float32) - vx_stable_shift_stationary(mid_date)float32-42.8 8.6 0.0 -2.1 ... 0.3 3.6 30.8
- description :
- vx shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vx_stable_shift_stationary
- units :
- meter/year
array([-4.280e+01, 8.600e+00, 0.000e+00, -2.100e+00, 1.000e+00, 8.000e-01, -8.550e+01, 0.000e+00, 0.000e+00, -1.220e+01, 2.100e+00, 9.000e-01, 1.220e+01, -7.000e-01, -4.280e+01, 0.000e+00, 0.000e+00, -2.200e+00, 3.970e+01, 0.000e+00, 0.000e+00, 2.640e+01, 0.000e+00, 0.000e+00, 0.000e+00, 1.430e+01, 0.000e+00, 0.000e+00, 0.000e+00, 1.300e+00, -1.400e+00, -6.000e-01, -4.280e+01, 1.500e+00, 0.000e+00, 6.000e-01, 1.830e+01, 8.600e+00, -1.100e+00, -8.000e-01, 0.000e+00, 1.400e+00, 0.000e+00, 8.000e-01, -1.200e+00, 0.000e+00, -8.000e-01, 0.000e+00, -9.000e-01, -8.000e-01, 1.400e+00, -8.000e-01, 5.300e+00, 1.700e+00, -2.000e-01, -4.000e-01, 1.220e+01, 9.000e-01, 4.900e+00, 2.000e-01, 1.300e+00, 7.300e+00, -4.000e+00, 0.000e+00, 1.100e+00, 8.000e-01, -1.300e+00, -5.300e+00, -2.000e-01, 0.000e+00, 0.000e+00, 5.000e-01, 1.300e+00, 2.900e+00, 0.000e+00, 0.000e+00, 0.000e+00, -4.300e+00, -1.200e+00, -4.930e+01, 0.000e+00, 0.000e+00, 6.000e-01, 1.500e+00, 0.000e+00, -5.000e-01, -8.000e-01, 2.100e+00, -3.600e+00, 1.170e+01, 0.000e+00, 3.500e+00, 4.280e+01, 0.000e+00, 0.000e+00, -9.500e+00, 8.600e+00, 0.000e+00, 4.000e-01, 7.100e+00, ... 1.200e+00, -3.100e+00, 7.700e+00, -1.000e-01, -8.000e-01, 1.680e+01, 6.000e-01, 9.600e+00, 8.000e-01, -5.300e+00, -1.100e+00, 4.400e+00, -3.400e+00, -1.600e+00, 2.450e+01, 9.200e+00, 1.000e+00, 1.430e+01, 1.300e+00, 8.000e-01, 3.800e+00, -2.000e-01, 2.600e+00, 0.000e+00, 5.300e+00, 9.000e-01, 1.500e+00, 6.500e+00, 0.000e+00, 2.600e+00, 0.000e+00, 7.600e+00, 1.400e+00, 1.100e+00, 1.700e+00, 3.200e+00, 9.600e+00, 0.000e+00, 1.610e+01, -1.400e+00, 1.300e+00, -1.300e+00, 9.200e+00, 0.000e+00, -8.100e+00, 4.100e+00, 1.200e+01, 0.000e+00, 1.900e+00, -4.000e-01, -1.000e-01, 1.400e+01, 2.100e+00, 1.200e+00, 2.000e-01, 3.100e+00, -1.400e+00, 0.000e+00, 2.700e+00, 8.000e-01, 1.000e+00, 9.800e+00, 8.300e+00, 2.850e+01, 7.000e-01, 5.000e+00, -3.000e-01, 6.500e+00, 8.100e+00, 1.400e+00, -1.200e+00, 6.200e+00, -1.900e+00, 6.000e-01, 1.020e+01, 7.000e-01, 8.190e+01, 7.200e+00, 0.000e+00, -1.200e+00, 5.300e+00, -7.000e-01, 3.400e+00, 2.000e-01, -1.800e+00, 1.800e+00, 0.000e+00, -1.200e+00, 6.010e+01, -1.500e+00, 1.590e+01, 1.550e+01, 5.940e+01, -6.300e+00, 3.000e-01, 3.600e+00, 3.080e+01], dtype=float32) - vy(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity component in y direction
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_y_velocity
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - vy_error(mid_date)float32112.5 37.6 54.2 ... 8.9 11.3 25.4
- description :
- best estimate of y_velocity error: vy_error is populated according to the approach used for the velocity bias correction as indicated in "stable_shift_flag"
- standard_name :
- vy_error
- units :
- meter/year
array([112.5, 37.6, 54.2, 5.9, 6. , 2.2, 150.3, 3.4, 134.7, 27.4, 4.2, 5.7, 27.9, 5.4, 410.3, 4.6, 4.6, 5.4, 72.9, 3.5, 6.6, 56. , 6. , 15.8, 22.5, 64.8, 5.1, 4.5, 3.5, 5.2, 4.3, 4.3, 145.8, 4.5, 4.3, 5. , 29.5, 39.5, 8.6, 3.5, 2.9, 3.3, 3.6, 2.6, 5.1, 3.4, 4. , 3.6, 7.4, 6.5, 6.3, 3.6, 14.3, 5.1, 4.2, 8.1, 36. , 5.6, 209. , 2.7, 10.6, 37. , 5.5, 5.5, 3.9, 2.5, 3.7, 28. , 33.9, 3.5, 4. , 5.3, 4.5, 7.9, 16.2, 2.5, 15.6, 5.2, 12.4, 58.8, 4.5, 4.6, 6.3, 13.7, 180. , 4.6, 4.5, 5.9, 19.5, 27.7, 22.5, 6.1, 157.8, 37.3, 4. , 21.6, 33.8, 4.5, 3.8, 18.3, 4.4, 3.8, 3. , 7.6, 3.5, 5.4, 25.8, 2.3, 29.3, 4.2, 6.1, 20.1, 53. , 3. , 20.2, 23.2, 2.6, 3. , 3. , 57.5, 51.9, 57.1, 12.2, 12.5, 48. , 3.6, 4.3, 32.4, 2.5, 11.6, 5.4, 24. , 58.1, 4. , 13.6, 16.1, 4.6, 19.2, 4.2, 48.9, 3.6, 4.6, 6.1, 18.5, 4.3, 14. , 27.6, 4.4, 26.8, 6.9, 16.5, 146.6, 33.6, 166.6, 26.8, 4.1, 63.7, 27.2, 5.2, 16.8, 3.3, 20.5, 3. , 10.9, 3.4, 58.9, 3.9, 4.2, 3.6, 3.3, 4.8, 21.5, 3.5, 5.9, 3.2, 3. , 3.6, 2.9, 25.1, 3.7, ... 5.9, 5.8, 4. , 3.7, 36.8, 11.1, 11.1, 19.4, 15.8, 6.6, 4.7, 1.7, 9.8, 2.9, 5.2, 3.3, 6.2, 5.6, 10.4, 5.6, 5.8, 6.6, 23.8, 24.8, 4.5, 4.3, 6.7, 6.5, 10. , 10.4, 5. , 3.2, 9.3, 161.1, 4.2, 16.6, 6.6, 4. , 13.8, 12.6, 3.9, 12.2, 5.3, 16.6, 5.9, 17.4, 18.7, 3.7, 31.2, 3.9, 16.4, 8.3, 16.8, 1.3, 17.6, 12. , 22.9, 7.7, 3.6, 17.5, 14.4, 8.5, 3.3, 5.4, 8.6, 2.5, 3.3, 2.9, 11.1, 4.7, 12.2, 21.6, 8.2, 7.6, 11.1, 7.2, 13.7, 7.2, 2.4, 3.5, 11.2, 28.6, 9. , 5.4, 14. , 8.7, 6.3, 5. , 22.6, 3.6, 3.5, 22.2, 5.7, 33.4, 61.6, 4.8, 31.9, 6.4, 5.7, 3.8, 14.8, 7.1, 3.7, 3.7, 2.9, 6.3, 5.7, 2.8, 6. , 3.3, 11.7, 3.9, 4.5, 18.3, 20.9, 62.2, 8.2, 23. , 7.4, 3.1, 10. , 9.7, 3.3, 12.5, 3.8, 17.1, 6.7, 5.4, 4.4, 13.7, 16.9, 7.1, 3.5, 15.8, 5.9, 6.2, 3.2, 12. , 12.7, 2.8, 9.8, 6. , 98.9, 5.5, 14.3, 6.5, 18.8, 3.5, 4.2, 13.9, 8.2, 8.4, 2.6, 10.1, 3.2, 33.7, 17.2, 3.9, 6.8, 11.2, 5.2, 19.3, 2.3, 22.2, 6.9, 8.3, 4.9, 19.2, 7.6, 11.9, 10.8, 17.6, 20.5, 8.9, 11.3, 25.4], dtype=float32) - vy_error_modeled(mid_date)float321.163e+03 232.7 ... 97.0 166.2
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vy_error_modeled
- units :
- meter/year
array([1163.2, 232.7, 387.9, 28.4, 27.1, 20.8, 1163.2, 26.4, 1163.2, 166.2, 24.8, 24.8, 166.2, 28.4, 1163.8, 25.9, 29.1, 27.1, 387.8, 25.3, 33.2, 387.8, 30.6, 116.3, 193.9, 387.9, 34.2, 18.8, 24.8, 25.9, 22. , 27.7, 1163.9, 23.7, 17.6, 22. , 166.2, 232.7, 29.8, 22.4, 23.3, 19.7, 20.8, 21.5, 32.3, 24.2, 22.8, 25.3, 23.7, 31.4, 38.8, 22.4, 89.5, 23.7, 22.8, 27.1, 232.7, 29.8, 1164. , 27.7, 36.4, 232.7, 31.4, 29.1, 29.1, 22.4, 21.5, 145.4, 166.2, 18.5, 17.6, 28.4, 21.2, 33.2, 145.4, 24.2, 97. , 29.8, 68.4, 387.8, 22.4, 26.4, 26.4, 41.6, 1163.9, 17.4, 22. , 32.3, 97. , 129.3, 105.8, 31.4, 1163.3, 581.7, 18.8, 129.3, 232.7, 20.8, 25.9, 193.9, 22.8, 23.7, 18.2, 35.3, 23.3, 21.5, 193.9, 24.2, 232.7, 24.8, 36.4, 64.6, 387.8, 21.5, 116.3, 116.3, 22.4, 25.3, 24.8, 387.9, 581.7, 581.7, 55.4, 97. , 581.7, 30.6, 21.5, 232.7, 23.3, 37.5, 23.7, 105.8, 387.8, 18.2, 145.4, 145.4, 23.3, 116.3, 20.4, 387.8, 29.1, 24.8, 27.7, 105.8, 20.1, 77.6, 193.9, 22.8, 166.2, 25.9, 52.9, 1163.2, 290.9, 1163.2, 145.4, 28.4, 581.7, 166.2, 30.6, 97. , ... 46.5, 22. , 38.8, 31.4, 129.3, 166.2, 27.1, 26.4, 38.8, 18.5, 72.7, 35.3, 17.4, 27.7, 43.1, 1163.2, 34.2, 145.4, 50.6, 20.4, 43.1, 83.1, 19.1, 64.6, 29.8, 89.5, 22.8, 68.4, 105.8, 19.7, 166.2, 17.1, 61.2, 35.3, 116.3, 25.3, 55.4, 64.6, 72.7, 40.1, 17.4, 97. , 61.2, 52.9, 20.1, 38.8, 37.5, 17.1, 17.9, 21.5, 61.2, 19.4, 68.4, 89.5, 64.6, 40.1, 46.5, 41.6, 77.6, 46.5, 29.1, 25.9, 83.1, 105.8, 33.2, 48.5, 68.4, 50.6, 37.5, 20.4, 61.2, 30.6, 29.8, 50.6, 19.7, 166.2, 232.7, 18.5, 129.3, 34.2, 19.1, 17.4, 83.1, 35.3, 19.4, 24.8, 24.2, 41.6, 35.3, 22.4, 44.7, 24.8, 46.5, 17.9, 20.4, 77.6, 77.6, 387.8, 48.5, 89.5, 38.8, 22.4, 64.6, 50.6, 27.7, 31.4, 17.4, 68.4, 41.6, 30.6, 17.6, 48.5, 55.4, 33.2, 32.3, 46.5, 21.2, 38.8, 18.8, 72.7, 83.1, 30.6, 50.6, 37.5, 387.8, 19.7, 40.1, 19.1, 77.6, 31.4, 22.8, 35.3, 46.5, 52.9, 17.1, 55.4, 17.6, 232.7, 68.4, 25.9, 34.2, 37.5, 28.4, 166.2, 17.6, 89.5, 58.2, 21.2, 20.4, 129.3, 22.8, 55.4, 40.1, 105.8, 105.8, 18.5, 97. , 166.2], dtype=float32) - vy_error_slow(mid_date)float32112.5 37.6 54.1 ... 8.9 11.3 25.4
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vy_error_slow
- units :
- meter/year
array([112.5, 37.6, 54.1, 5.9, 6. , 2.2, 150.3, 3.4, 134.7, 27.4, 4.2, 5.7, 27.9, 5.4, 409.5, 4.6, 4.6, 5.4, 72.8, 3.5, 6.6, 55.9, 6. , 15.8, 22.5, 64.7, 5.1, 4.5, 3.5, 5.2, 4.3, 4.3, 145.6, 4.5, 4.3, 5. , 29.4, 39.5, 8.6, 3.5, 2.9, 3.3, 3.6, 2.6, 5.1, 3.4, 4. , 3.6, 7.3, 6.5, 6.3, 3.6, 14.3, 5.1, 4.2, 8. , 36. , 5.6, 208.7, 2.7, 10.6, 36.9, 5.5, 5.5, 3.9, 2.5, 3.7, 28. , 33.9, 3.5, 4. , 5.3, 4.5, 7.9, 16.1, 2.4, 15.6, 5.2, 12.4, 58.7, 4.5, 4.6, 6.3, 13.7, 179.9, 4.6, 4.5, 5.9, 19.5, 27.7, 22.4, 6.1, 157.9, 37.4, 4. , 21.6, 33.8, 4.5, 3.8, 18.3, 4.4, 3.8, 3. , 7.6, 3.5, 5.4, 25.7, 2.3, 29.3, 4.2, 6.1, 20.1, 53. , 3. , 20.2, 23.2, 2.6, 3. , 3. , 57.5, 51.9, 57. , 12.2, 12.5, 48. , 3.6, 4.3, 32.4, 2.5, 11.6, 5.4, 24. , 58.1, 4. , 13.6, 16.1, 4.6, 19.2, 4.2, 48.9, 3.6, 4.6, 6.1, 18.5, 4.3, 14. , 27.6, 4.4, 26.8, 6.9, 16.5, 146.6, 33.6, 166.7, 26.8, 4.1, 63.6, 27.2, 5.2, 16.8, 3.3, 20.5, 3. , 10.9, 3.4, 58.8, 3.9, 4.2, 3.6, 3.3, 4.8, 21.5, 3.5, 5.9, 3.2, 3. , 3.6, 2.9, 25.1, 3.7, ... 5.9, 5.8, 4. , 3.7, 36.8, 11. , 11.2, 19.4, 15.8, 6.6, 4.7, 1.7, 9.8, 2.9, 5.2, 3.3, 6.2, 5.6, 10.4, 5.6, 5.8, 6.6, 23.8, 24.8, 4.5, 4.3, 6.7, 6.5, 10. , 10.4, 5. , 3.2, 9.3, 160.8, 4.2, 16.6, 6.6, 4. , 13.8, 12.6, 3.9, 12.2, 5.3, 16.6, 5.9, 17.5, 18.7, 3.7, 31.2, 3.9, 16.4, 8.3, 16.8, 1.3, 17.6, 12. , 22.9, 7.7, 3.6, 17.5, 14.4, 8.5, 3.3, 5.4, 8.6, 2.5, 3.3, 2.9, 11. , 4.7, 12.2, 21.6, 8.2, 7.6, 11.1, 7.2, 13.8, 7.2, 2.4, 3.5, 11.2, 28.6, 9. , 5.4, 14. , 8.7, 6.3, 5. , 22.6, 3.6, 3.5, 22.2, 5.7, 33.4, 61.5, 4.8, 31.9, 6.4, 5.7, 3.8, 14.8, 7.1, 3.7, 3.7, 2.9, 6.3, 5.7, 2.8, 6. , 3.3, 11.7, 3.9, 4.5, 18.3, 20.9, 62. , 8.1, 23.1, 7.4, 3.1, 10. , 9.7, 3.3, 12.5, 3.8, 17.1, 6.7, 5.4, 4.4, 13.7, 16.9, 7.1, 3.5, 15.8, 5.9, 6.2, 3.2, 12. , 12.7, 2.8, 9.8, 6. , 98.9, 5.5, 14.3, 6.5, 18.8, 3.5, 4.2, 13.9, 8.2, 8.4, 2.6, 10.1, 3.2, 33.7, 17.2, 3.9, 6.8, 11.2, 5.1, 19.3, 2.3, 22.2, 6.9, 8.2, 4.9, 19.2, 7.6, 11.9, 10.9, 17.6, 20.4, 8.9, 11.3, 25.4], dtype=float32) - vy_error_stationary(mid_date)float32112.5 37.6 54.2 ... 8.9 11.3 25.4
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 meter/year identified from an external mask
- standard_name :
- vy_error_stationary
- units :
- meter/year
array([112.5, 37.6, 54.2, 5.9, 6. , 2.2, 150.3, 3.4, 134.7, 27.4, 4.2, 5.7, 27.9, 5.4, 410.3, 4.6, 4.6, 5.4, 72.9, 3.5, 6.6, 56. , 6. , 15.8, 22.5, 64.8, 5.1, 4.5, 3.5, 5.2, 4.3, 4.3, 145.8, 4.5, 4.3, 5. , 29.5, 39.5, 8.6, 3.5, 2.9, 3.3, 3.6, 2.6, 5.1, 3.4, 4. , 3.6, 7.4, 6.5, 6.3, 3.6, 14.3, 5.1, 4.2, 8.1, 36. , 5.6, 209. , 2.7, 10.6, 37. , 5.5, 5.5, 3.9, 2.5, 3.7, 28. , 33.9, 3.5, 4. , 5.3, 4.5, 7.9, 16.2, 2.5, 15.6, 5.2, 12.4, 58.8, 4.5, 4.6, 6.3, 13.7, 180. , 4.6, 4.5, 5.9, 19.5, 27.7, 22.5, 6.1, 157.8, 37.3, 4. , 21.6, 33.8, 4.5, 3.8, 18.3, 4.4, 3.8, 3. , 7.6, 3.5, 5.4, 25.8, 2.3, 29.3, 4.2, 6.1, 20.1, 53. , 3. , 20.2, 23.2, 2.6, 3. , 3. , 57.5, 51.9, 57.1, 12.2, 12.5, 48. , 3.6, 4.3, 32.4, 2.5, 11.6, 5.4, 24. , 58.1, 4. , 13.6, 16.1, 4.6, 19.2, 4.2, 48.9, 3.6, 4.6, 6.1, 18.5, 4.3, 14. , 27.6, 4.4, 26.8, 6.9, 16.5, 146.6, 33.6, 166.6, 26.8, 4.1, 63.7, 27.2, 5.2, 16.8, 3.3, 20.5, 3. , 10.9, 3.4, 58.9, 3.9, 4.2, 3.6, 3.3, 4.8, 21.5, 3.5, 5.9, 3.2, 3. , 3.6, 2.9, 25.1, 3.7, ... 5.9, 5.8, 4. , 3.7, 36.8, 11.1, 11.1, 19.4, 15.8, 6.6, 4.7, 1.7, 9.8, 2.9, 5.2, 3.3, 6.2, 5.6, 10.4, 5.6, 5.8, 6.6, 23.8, 24.8, 4.5, 4.3, 6.7, 6.5, 10. , 10.4, 5. , 3.2, 9.3, 161.1, 4.2, 16.6, 6.6, 4. , 13.8, 12.6, 3.9, 12.2, 5.3, 16.6, 5.9, 17.4, 18.7, 3.7, 31.2, 3.9, 16.4, 8.3, 16.8, 1.3, 17.6, 12. , 22.9, 7.7, 3.6, 17.5, 14.4, 8.5, 3.3, 5.4, 8.6, 2.5, 3.3, 2.9, 11.1, 4.7, 12.2, 21.6, 8.2, 7.6, 11.1, 7.2, 13.7, 7.2, 2.4, 3.5, 11.2, 28.6, 9. , 5.4, 14. , 8.7, 6.3, 5. , 22.6, 3.6, 3.5, 22.2, 5.7, 33.4, 61.6, 4.8, 31.9, 6.4, 5.7, 3.8, 14.8, 7.1, 3.7, 3.7, 2.9, 6.3, 5.7, 2.8, 6. , 3.3, 11.7, 3.9, 4.5, 18.3, 20.9, 62.2, 8.2, 23. , 7.4, 3.1, 10. , 9.7, 3.3, 12.5, 3.8, 17.1, 6.7, 5.4, 4.4, 13.7, 16.9, 7.1, 3.5, 15.8, 5.9, 6.2, 3.2, 12. , 12.7, 2.8, 9.8, 6. , 98.9, 5.5, 14.3, 6.5, 18.8, 3.5, 4.2, 13.9, 8.2, 8.4, 2.6, 10.1, 3.2, 33.7, 17.2, 3.9, 6.8, 11.2, 5.2, 19.3, 2.3, 22.2, 6.9, 8.3, 4.9, 19.2, 7.6, 11.9, 10.8, 17.6, 20.5, 8.9, 11.3, 25.4], dtype=float32) - vy_stable_shift(mid_date)float32-74.2 -25.7 -28.5 ... -3.6 -10.8
- description :
- applied vy shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vy_stable_shift
- units :
- meter/year
array([-7.420e+01, -2.570e+01, -2.850e+01, -8.000e-01, -2.600e+00, 0.000e+00, -8.550e+01, 0.000e+00, 0.000e+00, -7.900e+00, 3.000e-01, -3.600e+00, -3.730e+01, -1.600e+00, -2.139e+02, -2.900e+00, 0.000e+00, 0.000e+00, 1.100e+00, 0.000e+00, 0.000e+00, 2.850e+01, 0.000e+00, -4.300e+00, 0.000e+00, -2.850e+01, 1.100e+00, 2.800e+00, 0.000e+00, -4.900e+00, -1.200e+00, 1.000e+00, -8.550e+01, 9.000e-01, 2.300e+00, -3.000e+00, -8.000e-01, 2.120e+01, -4.800e+00, 1.600e+00, 9.000e-01, 0.000e+00, -8.000e-01, 8.000e-01, 1.200e+00, -2.000e-01, -2.000e+00, -9.000e-01, -5.000e+00, 4.000e-01, -5.600e+00, 3.300e+00, 0.000e+00, -6.000e+00, 9.000e-01, -6.800e+00, -4.280e+01, -1.100e+00, -2.456e+02, -1.500e+00, -4.000e+00, -1.550e+01, -1.300e+00, 0.000e+00, -2.100e+00, 8.000e-01, 4.000e+00, 2.140e+01, 6.800e+00, 0.000e+00, -1.000e+00, -1.000e+00, -5.200e+00, -9.800e+00, 0.000e+00, 0.000e+00, 1.430e+01, -1.100e+00, 0.000e+00, -2.340e+01, 1.600e+00, -1.000e+00, 0.000e+00, -6.100e+00, -4.280e+01, -4.000e-01, 1.800e+00, -5.900e+00, 1.090e+01, 1.460e+01, 3.500e+00, -1.370e+01, 0.000e+00, 0.000e+00, 7.000e-01, -1.450e+01, -1.700e+00, 1.500e+00, 0.000e+00, 0.000e+00, ... 7.000e-01, 3.100e+00, -2.600e+00, -3.700e+00, 5.000e-01, 2.200e+00, 0.000e+00, -2.000e+00, -3.600e+00, -3.000e+00, 9.000e-01, 5.000e-01, -1.080e+01, 2.200e+00, -1.130e+01, -4.800e+00, -1.400e+00, -4.900e+00, -1.300e+00, -1.400e+00, -1.600e+00, 6.900e+00, 4.900e+00, 0.000e+00, -4.300e+00, -6.000e-01, -1.500e+00, 2.200e+00, 0.000e+00, -8.000e-01, 9.000e-01, -3.600e+00, -7.000e-01, -1.000e-01, -3.000e+00, -1.500e+00, 7.100e+00, 1.800e+00, -9.100e+00, 0.000e+00, -1.000e+00, 0.000e+00, -3.700e+00, -1.200e+00, -8.100e+00, -3.700e+00, -5.000e+00, 1.500e+00, -1.400e+00, 0.000e+00, -1.800e+00, -6.000e+00, -3.700e+00, 1.200e+00, 5.000e-01, -1.200e+00, 3.900e+00, -7.000e-01, -2.700e+00, -2.000e-01, 0.000e+00, -3.700e+00, 1.900e+00, -2.850e+01, -1.400e+00, -1.000e-01, -1.400e+00, -1.160e+01, 0.000e+00, -1.200e+00, 4.000e-01, -2.700e+00, -5.100e+00, -6.000e-01, -4.000e+00, -8.000e-01, -9.300e+00, -1.010e+01, 1.900e+00, -1.300e+00, -7.200e+00, -2.100e+00, 5.000e+00, -6.000e-01, 6.100e+00, 2.100e+00, -1.400e+01, 1.500e+00, -1.080e+01, -6.700e+00, -1.200e+01, -4.400e+00, -1.210e+01, 2.700e+00, -3.300e+00, -3.600e+00, -1.080e+01], dtype=float32) - vy_stable_shift_slow(mid_date)float32-73.8 -25.7 -28.5 ... -3.6 -10.7
- description :
- vy shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vy_stable_shift_slow
- units :
- meter/year
array([-7.380e+01, -2.570e+01, -2.850e+01, -7.000e-01, -2.600e+00, 0.000e+00, -8.550e+01, 0.000e+00, 0.000e+00, -7.900e+00, 3.000e-01, -3.600e+00, -3.720e+01, -1.600e+00, -2.139e+02, -2.900e+00, 0.000e+00, 0.000e+00, 1.200e+00, 0.000e+00, 0.000e+00, 2.850e+01, 0.000e+00, -4.300e+00, 0.000e+00, -2.850e+01, 1.100e+00, 2.800e+00, 0.000e+00, -4.900e+00, -1.200e+00, 1.000e+00, -8.550e+01, 9.000e-01, 2.300e+00, -3.000e+00, -8.000e-01, 2.110e+01, -4.800e+00, 1.600e+00, 9.000e-01, 0.000e+00, -8.000e-01, 8.000e-01, 1.200e+00, -2.000e-01, -2.000e+00, -9.000e-01, -5.000e+00, 4.000e-01, -5.700e+00, 3.300e+00, 0.000e+00, -6.000e+00, 9.000e-01, -6.800e+00, -4.280e+01, -1.100e+00, -2.458e+02, -1.500e+00, -4.000e+00, -1.550e+01, -1.300e+00, 0.000e+00, -2.100e+00, 8.000e-01, 4.000e+00, 2.140e+01, 6.800e+00, 0.000e+00, -1.000e+00, -1.000e+00, -5.200e+00, -9.800e+00, 0.000e+00, 0.000e+00, 1.430e+01, -1.100e+00, 0.000e+00, -2.340e+01, 1.600e+00, -1.000e+00, 0.000e+00, -6.100e+00, -4.280e+01, -5.000e-01, 1.800e+00, -5.900e+00, 1.100e+01, 1.470e+01, 3.500e+00, -1.380e+01, 0.000e+00, 0.000e+00, 7.000e-01, -1.450e+01, -1.800e+00, 1.500e+00, 0.000e+00, 0.000e+00, ... 7.000e-01, 3.100e+00, -2.500e+00, -3.700e+00, 5.000e-01, 2.200e+00, 0.000e+00, -2.000e+00, -3.600e+00, -3.000e+00, 9.000e-01, 5.000e-01, -1.070e+01, 2.200e+00, -1.140e+01, -4.200e+00, -1.400e+00, -4.800e+00, -1.300e+00, -1.400e+00, -1.600e+00, 7.100e+00, 4.900e+00, 0.000e+00, -4.300e+00, -6.000e-01, -1.500e+00, 2.200e+00, 0.000e+00, -8.000e-01, 9.000e-01, -3.600e+00, -7.000e-01, -1.000e-01, -3.000e+00, -1.500e+00, 7.500e+00, 1.800e+00, -9.100e+00, 0.000e+00, -1.000e+00, 0.000e+00, -3.700e+00, -1.200e+00, -8.100e+00, -3.700e+00, -5.000e+00, 1.500e+00, -1.400e+00, 0.000e+00, -1.900e+00, -6.000e+00, -3.700e+00, 1.200e+00, 6.000e-01, -1.200e+00, 3.900e+00, -7.000e-01, -2.700e+00, -2.000e-01, 0.000e+00, -3.700e+00, 1.900e+00, -2.850e+01, -1.400e+00, -1.000e-01, -1.400e+00, -1.150e+01, 0.000e+00, -1.200e+00, 4.000e-01, -2.700e+00, -5.100e+00, -6.000e-01, -4.100e+00, -8.000e-01, -9.300e+00, -1.010e+01, 1.900e+00, -1.300e+00, -7.100e+00, -2.100e+00, 5.000e+00, -6.000e-01, 6.000e+00, 2.100e+00, -1.400e+01, 1.500e+00, -1.070e+01, -6.700e+00, -1.200e+01, -4.300e+00, -1.200e+01, 2.800e+00, -3.300e+00, -3.600e+00, -1.070e+01], dtype=float32) - vy_stable_shift_stationary(mid_date)float32-74.2 -25.7 -28.5 ... -3.6 -10.8
- description :
- vy shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vy_stable_shift_stationary
- units :
- meter/year
array([-7.420e+01, -2.570e+01, -2.850e+01, -8.000e-01, -2.600e+00, 0.000e+00, -8.550e+01, 0.000e+00, 0.000e+00, -7.900e+00, 3.000e-01, -3.600e+00, -3.730e+01, -1.600e+00, -2.139e+02, -2.900e+00, 0.000e+00, 0.000e+00, 1.100e+00, 0.000e+00, 0.000e+00, 2.850e+01, 0.000e+00, -4.300e+00, 0.000e+00, -2.850e+01, 1.100e+00, 2.800e+00, 0.000e+00, -4.900e+00, -1.200e+00, 1.000e+00, -8.550e+01, 9.000e-01, 2.300e+00, -3.000e+00, -8.000e-01, 2.120e+01, -4.800e+00, 1.600e+00, 9.000e-01, 0.000e+00, -8.000e-01, 8.000e-01, 1.200e+00, -2.000e-01, -2.000e+00, -9.000e-01, -5.000e+00, 4.000e-01, -5.600e+00, 3.300e+00, 0.000e+00, -6.000e+00, 9.000e-01, -6.800e+00, -4.280e+01, -1.100e+00, -2.456e+02, -1.500e+00, -4.000e+00, -1.550e+01, -1.300e+00, 0.000e+00, -2.100e+00, 8.000e-01, 4.000e+00, 2.140e+01, 6.800e+00, 0.000e+00, -1.000e+00, -1.000e+00, -5.200e+00, -9.800e+00, 0.000e+00, 0.000e+00, 1.430e+01, -1.100e+00, 0.000e+00, -2.340e+01, 1.600e+00, -1.000e+00, 0.000e+00, -6.100e+00, -4.280e+01, -4.000e-01, 1.800e+00, -5.900e+00, 1.090e+01, 1.460e+01, 3.500e+00, -1.370e+01, 0.000e+00, 0.000e+00, 7.000e-01, -1.450e+01, -1.700e+00, 1.500e+00, 0.000e+00, 0.000e+00, ... 7.000e-01, 3.100e+00, -2.600e+00, -3.700e+00, 5.000e-01, 2.200e+00, 0.000e+00, -2.000e+00, -3.600e+00, -3.000e+00, 9.000e-01, 5.000e-01, -1.080e+01, 2.200e+00, -1.130e+01, -4.800e+00, -1.400e+00, -4.900e+00, -1.300e+00, -1.400e+00, -1.600e+00, 6.900e+00, 4.900e+00, 0.000e+00, -4.300e+00, -6.000e-01, -1.500e+00, 2.200e+00, 0.000e+00, -8.000e-01, 9.000e-01, -3.600e+00, -7.000e-01, -1.000e-01, -3.000e+00, -1.500e+00, 7.100e+00, 1.800e+00, -9.100e+00, 0.000e+00, -1.000e+00, 0.000e+00, -3.700e+00, -1.200e+00, -8.100e+00, -3.700e+00, -5.000e+00, 1.500e+00, -1.400e+00, 0.000e+00, -1.800e+00, -6.000e+00, -3.700e+00, 1.200e+00, 5.000e-01, -1.200e+00, 3.900e+00, -7.000e-01, -2.700e+00, -2.000e-01, 0.000e+00, -3.700e+00, 1.900e+00, -2.850e+01, -1.400e+00, -1.000e-01, -1.400e+00, -1.160e+01, 0.000e+00, -1.200e+00, 4.000e-01, -2.700e+00, -5.100e+00, -6.000e-01, -4.000e+00, -8.000e-01, -9.300e+00, -1.010e+01, 1.900e+00, -1.300e+00, -7.200e+00, -2.100e+00, 5.000e+00, -6.000e-01, 6.100e+00, 2.100e+00, -1.400e+01, 1.500e+00, -1.080e+01, -6.700e+00, -1.200e+01, -4.400e+00, -1.210e+01, 2.700e+00, -3.300e+00, -3.600e+00, -1.080e+01], dtype=float32)
- mid_datePandasIndex
PandasIndex(DatetimeIndex(['2017-12-25 04:11:40.527109888', '2018-12-12 04:08:03.179142912', '2018-12-04 04:08:17.320696064', '2017-07-18 04:11:34.949195008', '2018-07-13 04:08:04.816436992', '2019-07-04 04:10:27.618160896', '2017-01-23 04:11:33.121705984', '2017-07-30 04:10:28.475568128', '2017-11-07 04:11:55.447443968', '2017-12-01 04:11:43.316209920', ... '2018-03-15 04:08:53.730741248', '2018-06-19 04:09:27.910211072', '2018-04-08 04:08:58.818386944', '2017-12-09 04:11:12.435494912', '2018-03-31 04:10:01.464065024', '2018-06-11 04:09:32.921265664', '2017-09-12 04:11:46.053865984', '2017-06-24 04:11:18.708142080', '2017-05-27 04:10:08.145324032', '2017-05-07 04:11:30.865388288'], dtype='datetime64[ns]', name='mid_date', length=662, freq=None)) - xPandasIndex
PandasIndex(Index([700252.5, 700372.5, 700492.5, 700612.5, 700732.5, 700852.5, 700972.5, 701092.5, 701212.5, 701332.5, 701452.5, 701572.5, 701692.5, 701812.5, 701932.5, 702052.5, 702172.5, 702292.5, 702412.5, 702532.5, 702652.5, 702772.5, 702892.5, 703012.5, 703132.5, 703252.5, 703372.5, 703492.5, 703612.5, 703732.5, 703852.5, 703972.5, 704092.5, 704212.5, 704332.5, 704452.5, 704572.5, 704692.5, 704812.5, 704932.5, 705052.5, 705172.5, 705292.5, 705412.5, 705532.5, 705652.5, 705772.5, 705892.5, 706012.5, 706132.5, 706252.5, 706372.5, 706492.5, 706612.5, 706732.5, 706852.5, 706972.5, 707092.5, 707212.5, 707332.5, 707452.5, 707572.5, 707692.5, 707812.5, 707932.5, 708052.5, 708172.5, 708292.5, 708412.5, 708532.5, 708652.5, 708772.5, 708892.5], dtype='float64', name='x')) - yPandasIndex
PandasIndex(Index([3394627.5, 3394507.5, 3394387.5, 3394267.5, 3394147.5, 3394027.5, 3393907.5, 3393787.5, 3393667.5, 3393547.5, 3393427.5, 3393307.5, 3393187.5, 3393067.5, 3392947.5, 3392827.5, 3392707.5, 3392587.5, 3392467.5, 3392347.5, 3392227.5, 3392107.5, 3391987.5, 3391867.5, 3391747.5, 3391627.5, 3391507.5, 3391387.5, 3391267.5, 3391147.5, 3391027.5, 3390907.5, 3390787.5, 3390667.5, 3390547.5, 3390427.5, 3390307.5, 3390187.5, 3390067.5, 3389947.5, 3389827.5, 3389707.5, 3389587.5, 3389467.5, 3389347.5, 3389227.5, 3389107.5, 3388987.5, 3388867.5, 3388747.5, 3388627.5, 3388507.5, 3388387.5, 3388267.5, 3388147.5, 3388027.5, 3387907.5, 3387787.5, 3387667.5, 3387547.5, 3387427.5, 3387307.5, 3387187.5, 3387067.5], dtype='float64', name='y'))
- Conventions :
- CF-1.8
- GDAL_AREA_OR_POINT :
- Area
- author :
- ITS_LIVE, a NASA MEaSUREs project (its-live.jpl.nasa.gov)
- autoRIFT_parameter_file :
- http://its-live-data.s3.amazonaws.com/autorift_parameters/v001/autorift_landice_0120m.shp
- datacube_software_version :
- 1.0
- date_created :
- 25-Sep-2023 22:00:23
- date_updated :
- 25-Sep-2023 22:00:23
- geo_polygon :
- [[95.06959008486952, 29.814255053135895], [95.32812062059084, 29.809951334550703], [95.58659184122865, 29.80514261876954], [95.84499718862224, 29.7998293459177], [96.10333011481168, 29.79401200205343], [96.11032804508507, 30.019297601073085], [96.11740568350054, 30.244573983323825], [96.12456379063154, 30.469841094022847], [96.1318031397002, 30.695098878594504], [95.87110827645229, 30.70112924501256], [95.61033817656023, 30.7066371044805], [95.34949964126946, 30.711621947056347], [95.08859948278467, 30.716083310981194], [95.08376623410525, 30.49063893600811], [95.07898726183609, 30.26518607254204], [95.0742620484426, 30.039724763743482], [95.06959008486952, 29.814255053135895]]
- institution :
- NASA Jet Propulsion Laboratory (JPL), California Institute of Technology
- latitude :
- 30.26
- longitude :
- 95.6
- proj_polygon :
- [[700000, 3300000], [725000.0, 3300000.0], [750000.0, 3300000.0], [775000.0, 3300000.0], [800000, 3300000], [800000.0, 3325000.0], [800000.0, 3350000.0], [800000.0, 3375000.0], [800000, 3400000], [775000.0, 3400000.0], [750000.0, 3400000.0], [725000.0, 3400000.0], [700000, 3400000], [700000.0, 3375000.0], [700000.0, 3350000.0], [700000.0, 3325000.0], [700000, 3300000]]
- projection :
- 32646
- s3 :
- s3://its-live-data/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.zarr
- skipped_granules :
- s3://its-live-data/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.json
- time_standard_img1 :
- UTC
- time_standard_img2 :
- UTC
- title :
- ITS_LIVE datacube of image pair velocities
- url :
- https://its-live-data.s3.amazonaws.com/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.zarr
We can see that we are looking at roughly a third of the original time steps. Let’s take a look at the average speeds of the Landsat8-derived velocities:
l8_subset.v.mean(dim='mid_date').plot();
What about Landsat7?
l7_condition = sample_glacier_raster.satellite_img1 == '7'
l7_subset = sample_glacier_raster.sel(mid_date=l7_condition)
l7_subset
<xarray.Dataset>
Dimensions: (mid_date: 803, y: 64, x: 73)
Coordinates:
* mid_date (mid_date) datetime64[ns] 2017-11-11T04:11:45...
* x (x) float64 7.003e+05 7.004e+05 ... 7.089e+05
* y (y) float64 3.395e+06 3.395e+06 ... 3.387e+06
mapping int64 0
Data variables: (12/59)
M11 (mid_date, y, x) float32 nan nan nan ... nan nan
M11_dr_to_vr_factor (mid_date) float32 nan nan nan ... nan nan nan
M12 (mid_date, y, x) float32 nan nan nan ... nan nan
M12_dr_to_vr_factor (mid_date) float32 nan nan nan ... nan nan nan
acquisition_date_img1 (mid_date) datetime64[ns] 2017-05-03T04:12:55...
acquisition_date_img2 (mid_date) datetime64[ns] 2018-05-22T04:10:35...
... ...
vy_error_modeled (mid_date) float32 24.2 24.2 21.5 ... 46.5 46.5
vy_error_slow (mid_date) float32 4.3 5.0 3.4 ... 23.3 6.6 9.7
vy_error_stationary (mid_date) float32 4.3 5.0 3.4 ... 23.3 6.6 9.7
vy_stable_shift (mid_date) float32 -0.3 3.2 -0.8 ... 10.8 3.4
vy_stable_shift_slow (mid_date) float32 -0.3 3.2 -0.8 ... 10.8 3.4
vy_stable_shift_stationary (mid_date) float32 -0.3 3.2 -0.8 ... 10.8 3.4
Attributes: (12/19)
Conventions: CF-1.8
GDAL_AREA_OR_POINT: Area
author: ITS_LIVE, a NASA MEaSUREs project (its-live.j...
autoRIFT_parameter_file: http://its-live-data.s3.amazonaws.com/autorif...
datacube_software_version: 1.0
date_created: 25-Sep-2023 22:00:23
... ...
s3: s3://its-live-data/datacubes/v2/N30E090/ITS_L...
skipped_granules: s3://its-live-data/datacubes/v2/N30E090/ITS_L...
time_standard_img1: UTC
time_standard_img2: UTC
title: ITS_LIVE datacube of image pair velocities
url: https://its-live-data.s3.amazonaws.com/datacu...- mid_date: 803
- y: 64
- x: 73
- mid_date(mid_date)datetime64[ns]2017-11-11T04:11:45.280933120 .....
- description :
- midpoint of image 1 and image 2 acquisition date and time with granule's centroid longitude and latitude as microseconds
- standard_name :
- image_pair_center_date_with_time_separation
array(['2017-11-11T04:11:45.280933120', '2017-07-22T04:12:25.815367936', '2017-06-12T04:12:45.944154112', ..., '2017-07-26T04:11:49.029760256', '2017-04-21T04:11:32.560144896', '2018-06-11T04:10:57.953189888'], dtype='datetime64[ns]') - x(x)float647.003e+05 7.004e+05 ... 7.089e+05
- description :
- x coordinate of projection
- standard_name :
- projection_x_coordinate
- axis :
- X
- long_name :
- x coordinate of projection
- units :
- metre
array([700252.5, 700372.5, 700492.5, 700612.5, 700732.5, 700852.5, 700972.5, 701092.5, 701212.5, 701332.5, 701452.5, 701572.5, 701692.5, 701812.5, 701932.5, 702052.5, 702172.5, 702292.5, 702412.5, 702532.5, 702652.5, 702772.5, 702892.5, 703012.5, 703132.5, 703252.5, 703372.5, 703492.5, 703612.5, 703732.5, 703852.5, 703972.5, 704092.5, 704212.5, 704332.5, 704452.5, 704572.5, 704692.5, 704812.5, 704932.5, 705052.5, 705172.5, 705292.5, 705412.5, 705532.5, 705652.5, 705772.5, 705892.5, 706012.5, 706132.5, 706252.5, 706372.5, 706492.5, 706612.5, 706732.5, 706852.5, 706972.5, 707092.5, 707212.5, 707332.5, 707452.5, 707572.5, 707692.5, 707812.5, 707932.5, 708052.5, 708172.5, 708292.5, 708412.5, 708532.5, 708652.5, 708772.5, 708892.5]) - y(y)float643.395e+06 3.395e+06 ... 3.387e+06
- description :
- y coordinate of projection
- standard_name :
- projection_y_coordinate
- axis :
- Y
- long_name :
- y coordinate of projection
- units :
- metre
array([3394627.5, 3394507.5, 3394387.5, 3394267.5, 3394147.5, 3394027.5, 3393907.5, 3393787.5, 3393667.5, 3393547.5, 3393427.5, 3393307.5, 3393187.5, 3393067.5, 3392947.5, 3392827.5, 3392707.5, 3392587.5, 3392467.5, 3392347.5, 3392227.5, 3392107.5, 3391987.5, 3391867.5, 3391747.5, 3391627.5, 3391507.5, 3391387.5, 3391267.5, 3391147.5, 3391027.5, 3390907.5, 3390787.5, 3390667.5, 3390547.5, 3390427.5, 3390307.5, 3390187.5, 3390067.5, 3389947.5, 3389827.5, 3389707.5, 3389587.5, 3389467.5, 3389347.5, 3389227.5, 3389107.5, 3388987.5, 3388867.5, 3388747.5, 3388627.5, 3388507.5, 3388387.5, 3388267.5, 3388147.5, 3388027.5, 3387907.5, 3387787.5, 3387667.5, 3387547.5, 3387427.5, 3387307.5, 3387187.5, 3387067.5]) - mapping()int640
- crs_wkt :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- WGS 84
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- WGS 84 / UTM zone 46N
- grid_mapping_name :
- transverse_mercator
- latitude_of_projection_origin :
- 0.0
- longitude_of_central_meridian :
- 93.0
- false_easting :
- 500000.0
- false_northing :
- 0.0
- scale_factor_at_central_meridian :
- 0.9996
- spatial_ref :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- GeoTransform :
- 700192.5 120.0 0.0 3394687.5 0.0 -120.0
array(0)
- M11(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- conversion matrix element (1st row, 1st column) that can be multiplied with vx to give range pixel displacement dr (see Eq. A18 in https://www.mdpi.com/2072-4292/13/4/749)
- grid_mapping :
- mapping
- standard_name :
- conversion_matrix_element_11
- units :
- pixel/(meter/year)
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - M11_dr_to_vr_factor(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- multiplicative factor that converts slant range pixel displacement dr to slant range velocity vr
- standard_name :
- M11_dr_to_vr_factor
- units :
- meter/(year*pixel)
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - M12(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- conversion matrix element (1st row, 2nd column) that can be multiplied with vy to give range pixel displacement dr (see Eq. A18 in https://www.mdpi.com/2072-4292/13/4/749)
- grid_mapping :
- mapping
- standard_name :
- conversion_matrix_element_12
- units :
- pixel/(meter/year)
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - M12_dr_to_vr_factor(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- multiplicative factor that converts slant range pixel displacement dr to slant range velocity vr
- standard_name :
- M12_dr_to_vr_factor
- units :
- meter/(year*pixel)
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - acquisition_date_img1(mid_date)datetime64[ns]2017-05-03T04:12:55.171840 ... 2...
- description :
- acquisition date and time of image 1
- standard_name :
- image1_acquition_date
array(['2017-05-03T04:12:55.171840000', '2017-01-11T04:12:39.623214080', '2016-11-08T04:13:04.481691136', '2017-04-01T04:12:42.949755904', '2016-11-24T04:12:59.739601920', '2017-10-26T04:13:06.609417984', '2017-03-16T04:12:38.893263104', '2017-11-27T04:12:59.623030016', '2018-11-30T04:06:36.228204288', '2016-09-21T04:13:12.078295040', '2018-07-25T04:09:25.555763200', '2018-03-03T04:11:49.197383936', '2017-02-12T04:12:23.441945344', '2017-12-29T04:12:40.458198016', '2018-02-15T04:11:59.198033920', '2017-04-01T04:12:42.949755904', '2017-05-03T04:12:55.171840000', '2016-12-10T04:12:56.341405952', '2017-04-01T04:12:42.949755904', '2018-12-16T04:06:10.044793088', '2018-05-22T04:10:35.049019904', '2017-01-27T04:12:29.455911936', '2017-11-11T04:13:04.720666112', '2016-11-24T04:12:59.739601920', '2018-01-14T04:12:27.084400896', '2017-12-13T04:12:51.401551872', '2017-11-11T04:13:04.720666112', '2016-11-08T04:13:04.481691136', '2016-10-23T04:13:11.061116928', '2017-12-29T04:12:40.458198016', '2016-11-24T04:12:59.739601920', '2017-04-01T04:12:42.949755904', '2017-12-29T04:12:40.458198016', '2016-11-08T04:13:04.481691136', '2017-12-13T04:12:51.401551872', '2017-04-01T04:12:42.949755904', '2017-05-03T04:12:55.171840000', '2018-03-03T04:11:49.197383936', '2017-04-01T04:12:42.949755904', '2016-12-10T04:12:56.341405952', ... '2017-04-01T04:12:42.949755904', '2016-10-23T04:13:11.061116928', '2017-03-16T04:12:38.893263104', '2016-08-20T04:13:06.519042048', '2017-01-11T04:12:39.623214080', '2017-01-11T04:12:39.623214080', '2016-08-20T04:13:06.519042048', '2016-08-04T04:13:05.263087872', '2017-04-17T04:12:49.770447872', '2017-03-16T04:12:38.893263104', '2017-06-04T04:13:02.386535936', '2017-05-03T04:12:55.171840000', '2016-08-04T04:13:05.263087872', '2016-08-04T04:13:05.263087872', '2018-07-25T04:09:25.555763200', '2017-04-01T04:12:42.949755904', '2017-05-03T04:12:55.171840000', '2016-10-23T04:13:11.061116928', '2017-05-03T04:12:55.171840000', '2017-04-01T04:12:42.949755904', '2017-06-04T04:13:02.386535936', '2017-06-04T04:13:02.386535936', '2017-02-12T04:12:23.441945344', '2017-04-01T04:12:42.949755904', '2016-09-21T04:13:12.078295040', '2017-01-11T04:12:39.623214080', '2018-07-25T04:09:25.555763200', '2018-03-03T04:11:49.197383936', '2018-07-25T04:09:25.555763200', '2017-03-16T04:12:38.893263104', '2017-04-01T04:12:42.949755904', '2018-03-03T04:11:49.197383936', '2016-10-23T04:13:11.061116928', '2016-10-23T04:13:11.061116928', '2018-07-25T04:09:25.555763200', '2017-06-04T04:13:02.386535936', '2017-06-04T04:13:02.386535936', '2017-01-11T04:12:39.623214080', '2018-03-03T04:11:49.197383936'], dtype='datetime64[ns]') - acquisition_date_img2(mid_date)datetime64[ns]2018-05-22T04:10:35.049019904 .....
- description :
- acquisition date and time of image 2
- standard_name :
- image2_acquition_date
array(['2018-05-22T04:10:35.049019904', '2018-01-30T04:12:11.667300096', '2018-01-14T04:12:27.084400896', '2017-12-29T04:12:40.458198016', '2017-03-16T04:12:38.893263104', '2018-11-30T04:06:36.228204288', '2017-11-11T04:13:04.720666112', '2018-12-16T04:06:10.044793088', '2019-01-01T04:05:41.761686272', '2018-01-14T04:12:27.084400896', '2019-01-01T04:05:41.761686272', '2019-01-17T04:05:11.586401024', '2018-01-14T04:12:27.084400896', '2018-03-03T04:11:49.197383936', '2019-01-17T04:05:11.586401024', '2017-11-27T04:12:59.623030016', '2017-06-04T04:13:02.386535936', '2018-02-15T04:11:59.198033920', '2017-12-13T04:12:51.401551872', '2019-01-17T04:05:11.586401024', '2018-10-29T04:07:21.963168256', '2017-03-16T04:12:38.893263104', '2018-05-22T04:10:35.049019904', '2017-11-11T04:13:04.720666112', '2018-12-16T04:06:10.044793088', '2018-02-15T04:11:59.198033920', '2018-01-14T04:12:27.084400896', '2018-01-30T04:12:11.667300096', '2017-05-03T04:12:55.171840000', '2018-02-15T04:11:59.198033920', '2018-01-30T04:12:11.667300096', '2017-06-04T04:13:02.386535936', '2018-10-29T04:07:21.963168256', '2017-02-28T04:12:32.528041984', '2018-12-16T04:06:10.044793088', '2017-05-03T04:12:55.171840000', '2018-01-30T04:12:11.667300096', '2019-02-18T04:04:12.616978944', '2018-03-03T04:11:49.197383936', '2017-04-01T04:12:42.949755904', ... '2018-03-27T04:09:57.437323008', '2018-03-27T04:09:57.437323008', '2017-07-14T04:10:16.946407936', '2017-09-16T04:10:35.331774976', '2017-04-09T04:09:59.003422976', '2017-09-16T04:10:35.331774976', '2018-02-07T04:10:19.247780096', '2017-07-30T04:10:25.156854016', '2018-02-07T04:10:19.247780096', '2017-04-09T04:09:59.003422976', '2017-12-05T04:10:37.029957888', '2018-02-07T04:10:19.247780096', '2017-12-05T04:10:37.029957888', '2017-09-16T04:10:35.331774976', '2018-12-08T04:10:21.702228992', '2018-09-19T04:10:06.348390144', '2017-07-30T04:10:25.156854016', '2017-07-14T04:10:16.946407936', '2017-09-16T04:10:35.331774976', '2017-04-09T04:09:59.003422976', '2018-04-28T04:09:39.925913088', '2017-07-30T04:10:25.156854016', '2017-07-30T04:10:25.156854016', '2017-07-14T04:10:16.946407936', '2017-07-30T04:10:25.156854016', '2017-07-14T04:10:16.946407936', '2019-01-09T04:10:19.605915904', '2018-03-27T04:09:57.437323008', '2019-01-25T04:10:15.711925760', '2017-07-30T04:10:25.156854016', '2017-07-30T04:10:25.156854016', '2018-05-30T04:09:17.034597888', '2017-07-30T04:10:25.156854016', '2017-04-09T04:09:59.003422976', '2018-12-24T04:10:20.874892032', '2018-02-07T04:10:19.247780096', '2017-09-16T04:10:35.331774976', '2017-07-30T04:10:25.156854016', '2018-09-19T04:10:06.348390144'], dtype='datetime64[ns]') - autoRIFT_software_version(mid_date)object'1.5.0' '1.5.0' ... '1.5.0' '1.5.0'
- description :
- version of autoRIFT software
- standard_name :
- autoRIFT_software_version
array(['1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', ... '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0', '1.5.0'], dtype=object) - chip_size_height(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- chip_size_coordinates :
- Optical data: chip_size_coordinates = 'image projection geometry: width = x, height = y'. Radar data: chip_size_coordinates = 'radar geometry: width = range, height = azimuth'
- description :
- height of search template (chip)
- grid_mapping :
- mapping
- standard_name :
- chip_size_height
- units :
- m
- y_pixel_size :
- 10.0
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - chip_size_width(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- chip_size_coordinates :
- Optical data: chip_size_coordinates = 'image projection geometry: width = x, height = y'. Radar data: chip_size_coordinates = 'radar geometry: width = range, height = azimuth'
- description :
- width of search template (chip)
- grid_mapping :
- mapping
- standard_name :
- chip_size_width
- units :
- m
- x_pixel_size :
- 10.0
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - date_center(mid_date)datetime64[ns]2017-11-11T04:11:45.110430208 .....
- description :
- midpoint of image 1 and image 2 acquisition date
- standard_name :
- image_pair_center_date
array(['2017-11-11T04:11:45.110430208', '2017-07-22T04:12:25.645256960', '2017-06-12T04:12:45.783045888', '2017-08-15T04:12:41.703976960', '2017-01-19T04:12:49.316431872', '2018-05-14T04:09:51.418810880', '2017-07-14T04:12:51.806964992', '2018-06-07T04:09:34.833912064', '2018-12-16T04:06:08.994945024', '2017-05-19T04:12:49.581348096', '2018-10-13T04:07:33.658725376', '2018-08-10T04:08:30.391891968', '2017-07-30T04:12:25.263173120', '2018-01-30T04:12:14.827791104', '2018-08-02T04:08:35.392218112', '2017-07-30T04:12:51.286393088', '2017-05-19T04:12:58.779187968', '2017-07-14T04:12:27.769720064', '2017-08-07T04:12:47.175654144', '2019-01-01T04:05:40.815597056', '2018-08-10T04:08:58.506094080', '2017-02-20T04:12:34.174587904', '2018-02-15T04:11:49.884843264', '2017-05-19T04:13:02.230134016', '2018-07-01T04:09:18.564596992', '2018-01-14T04:12:25.299792896', '2017-12-13T04:12:45.902533888', '2017-06-20T04:12:38.074495232', '2017-01-27T04:13:03.116478976', '2018-01-22T04:12:19.828115968', '2017-06-28T04:12:35.703450880', '2017-05-03T04:12:52.668145920', '2018-05-30T04:10:01.210682880', '2017-01-03T04:12:48.504867328', '2018-06-15T04:09:30.723172096', '2017-04-17T04:12:49.060797952', '2017-09-16T04:12:33.419569664', '2018-08-26T04:08:00.907182080', '2017-09-16T04:12:16.073570048', '2017-02-04T04:12:49.645581056', ... '2017-09-28T04:11:20.193539840', '2017-07-10T04:11:34.249220096', '2017-05-15T04:11:27.919834880', '2017-03-04T04:11:50.925408000', '2017-02-24T04:11:19.313317888', '2017-05-15T04:11:37.477494016', '2017-05-15T04:11:42.883410944', '2017-01-31T04:11:45.209970944', '2017-09-12T04:11:34.509114112', '2017-03-28T04:11:18.948343040', '2017-09-04T04:11:49.708247040', '2017-09-20T04:11:37.209809920', '2017-04-05T04:11:51.146522880', '2017-02-24T04:11:50.297432064', '2018-10-01T04:09:53.628996096', '2017-12-25T04:11:24.649072896', '2017-06-16T04:11:40.164346880', '2017-03-04T04:11:44.003762944', '2017-07-10T04:11:45.251808000', '2017-04-05T04:11:20.976590336', '2017-11-15T04:11:21.156224000', '2017-07-02T04:11:43.771695104', '2017-05-07T04:11:24.299398912', '2017-05-23T04:11:29.948081920', '2017-02-24T04:11:48.617574912', '2017-04-13T04:11:28.284811008', '2018-10-17T04:09:52.580839168', '2018-03-15T04:10:53.317353984', '2018-10-25T04:09:50.633844992', '2017-05-23T04:11:32.025059072', '2017-05-31T04:11:34.053305088', '2018-04-16T04:10:33.115990784', '2017-03-12T04:11:48.108985344', '2017-01-15T04:11:35.032270080', '2018-10-09T04:09:53.215326976', '2017-10-06T04:11:40.817157888', '2017-07-26T04:11:48.859155968', '2017-04-21T04:11:32.390033920', '2018-06-11T04:10:57.772887040'], dtype='datetime64[ns]') - date_dt(mid_date)timedelta64[ns]383 days 23:57:40.253906252 ... ...
- description :
- time separation between acquisition of image 1 and image 2
- standard_name :
- image_pair_time_separation
array([33177460253906252, 33177570996093747, 37324763085937495, 23500797363281252, 9676778906250000, 34559609765625000, 20736026367187495, 33177191308593747, 2764745452880856, 41471955175781252, 13823775878906252, 27647601855468747, 29030402636718747, 5529548583984378, 29029991308593747, 20736017138671873, 2764807250976558, 37324741992187495, 22118407910156252, 2764741497802738, 13823807519531252, 4147209558105468, 16588649707031252, 30412805273437495, 29030022949218747, 5529547924804684, 5529562426757810, 38707147265625000, 16588784179687495, 4147158801269531, 37324752539062504, 5529619116210936, 26265280957031252, 9676768359375000, 31794799218750000, 2764812194824216, 23500757812500000, 30412343847656252, 29030347265625000, 9676786816406252, 2764780883789063, 27648021093750000, 44236705078125000, 24883115625000000, 27647649316406252, 31794780761718747, 35942349902343747, 29030009765625000, 11059068164062504, 2764786651611324, 33177570996093747, 5529551879882810, 4147219445800783, 1382373797607423, 29030062500000000, 27647638769531252, 33177565722656252, 29030410546875000, 2764775610351558, 2764771160888675, ... 6220660913085936, 40780657617187495, 22809515625000000, 18662170605468747, 38015796972656252, 25574225976562504, 36633394335937495, 31103775878906252, 4838270800781252, 28339020703125000, 4838440869140621, 43545396972656252, 13132665527343747, 8985432568359378, 29721439160156252, 14515058935546873, 14515072119140621, 29721386425781252, 4838255639648441, 25574312988281252, 31103833886718747, 44927804882812504, 10367858276367189, 33868649707031252, 7603039160156252, 21427076074218747, 46310231250000000, 31103839160156252, 25574249707031252, 2073440148925783, 15897454980468747, 24191844433593747, 42163052343750000, 35251049707031252, 11750456689453126, 46310241796875000, 7603049707031252, 22809425976562504, 11750260253906252, 691036070251464, 28338996972656252, 4838242785644531, 14515081347656252, 8985454321289063, 26956633886718747, 15897457617187495, 14515254052734378, 2073488269042972, 15897650097656252, 11750266845703126, 10367862231445315, 7603047729492189, 24191833886718747, 14515007519531252, 13132855371093747, 21427036523437495, 8985453002929684, 17279865527343747, 17279897167968747], dtype='timedelta64[ns]') - floatingice(y, x, mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- floating ice mask, 0 = non-floating-ice, 1 = floating-ice
- flag_meanings :
- non-ice ice
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- floating ice mask
- url :
- https://its-live-data.s3.amazonaws.com/autorift_parameters/v001/N46_0120m_floatingice.tif
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - granule_url(mid_date)object'https://its-live-data.s3.amazon...
- description :
- original granule URL
- standard_name :
- granule_url
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- description :
- light interpolation mask
- flag_meanings :
- measured interpolated
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- interpolated_value_mask
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - landice(y, x, mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- land ice mask, 0 = non-land-ice, 1 = land-ice
- flag_meanings :
- non-ice ice
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- land ice mask
- url :
- https://its-live-data.s3.amazonaws.com/autorift_parameters/v001/N46_0120m_landice.tif
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - mission_img1(mid_date)object'L' 'L' 'L' 'L' ... 'L' 'L' 'L' 'L'
- description :
- id of the mission that acquired image 1
- standard_name :
- image1_mission
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- description :
- id of the mission that acquired image 2
- standard_name :
- image2_mission
array(['L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', ... 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L', 'L'], dtype=object) - roi_valid_percentage(mid_date)float3214.0 16.9 18.0 16.0 ... 4.2 4.2 4.0
- description :
- percentage of pixels with a valid velocity estimate determined for the intersection of the full image pair footprint and the region of interest (roi) that defines where autoRIFT tried to estimate a velocity
- standard_name :
- region_of_interest_valid_pixel_percentage
array([14. , 16.9, 18. , 16. , 26.8, 26.2, 23.9, 62.3, 83. , 15. , 13.8, 12.7, 19. , 6.2, 69.6, 16.3, 21.3, 76.8, 19. , 89. , 3.4, 28.4, 23.9, 83. , 24.7, 49.4, 33. , 44. , 11.9, 66. , 53.2, 5.5, 37.9, 60.7, 54.6, 16. , 12.6, 6.6, 10. , 19.6, 54.9, 72. , 15.8, 24.9, 13.1, 76.8, 5.7, 56.7, 15.1, 67.2, 81.2, 19.9, 19. , 72. , 31.6, 58.8, 8.9, 24.6, 31. , 58. , 16.7, 17.6, 26.7, 31.1, 28.6, 88. , 69. , 12. , 21.7, 37.4, 21.9, 46.8, 20.7, 20.4, 48.5, 19.7, 23.5, 29.9, 7.8, 36.7, 31.7, 63.7, 25.7, 10. , 7.5, 25. , 20.5, 6.4, 20.5, 3.7, 13.6, 39.3, 26.3, 43.3, 20.5, 27.7, 8.5, 17.2, 10.3, 7.1, 19.8, 27.8, 44.5, 15.8, 46.7, 37.8, 7.2, 39.1, 55.9, 88. , 32. , 56.4, 33.9, 24.6, 17.5, 54. , 24.9, 28.4, 15. , 47.6, 29.4, 11.2, 36.7, 23.5, 11.5, 5.6, 9.2, 23.3, 18.9, 22.8, 58.9, 4.5, 51.9, 31. , 45.3, 19.9, 43.8, 16.8, 39.1, 25.4, 65.9, 44.6, 23.9, 18. , 8.6, 68.7, 17. , 25.5, 63.9, 20.3, 21.7, 31.9, 24.1, 7.1, 15.3, 5.6, 18.1, 62.9, 11. , 27.6, 18.3, 68.5, 26.3, 50. , 25.3, 5. , 18.9, 29.6, 15.1, 4.3, 48.6, 5.5, 72.6, 63. , 50.2, 46.2, 21. , 36.8, 13.4, 53. , 51.5, 34.7, 25. , 15.3, 3.5, 41.7, 34.1, 7.1, 74.2, 10.9, 3.2, 25.2, 18.1, 17.7, 19.7, 58. , 26.8, 12.7, 53. , 22.6, 8. , 62. , 20.4, 27.6, 80. , 11.2, 9.4, 8. , 47.1, 10.9, 11. , 15. , 19. , 51.9, 23.3, 33.8, 55.4, 17.3, 13.2, 32. , ... 29.9, 30.2, 29.1, 28.8, 28.6, 28.5, 28.9, 29.3, 29.2, 28.5, 28.9, 29.2, 28.6, 29.1, 28.8, 29.3, 27.8, 27.5, 28. , 27.6, 28.2, 28.4, 28.3, 27.6, 27.3, 27.1, 27.3, 26.9, 27.4, 26.8, 27. , 26. , 26.3, 26. , 26. , 26.1, 26.2, 26.4, 26.2, 26.1, 25.8, 26. , 25.8, 26.4, 25. , 25.3, 24.8, 25. , 24.6, 24.7, 24.9, 25. , 25.1, 23.8, 23.9, 24.2, 23.8, 23.6, 24.2, 23.9, 23.6, 24.4, 23.7, 23.8, 23.3, 23.3, 23.4, 23.1, 23.3, 22.7, 22.7, 23.1, 21.6, 22.3, 21.9, 21.5, 22. , 21.9, 21.7, 21.6, 22. , 22. , 21. , 21. , 21.3, 21.2, 21. , 20.8, 21. , 20.9, 20.7, 20.7, 21. , 20.7, 19.5, 19.9, 20.2, 19.9, 20.3, 19.9, 18.9, 19.3, 18.9, 18.9, 19.4, 19. , 19.4, 19.1, 18.7, 19. , 18.4, 18. , 18.2, 17.7, 18. , 17.8, 17.8, 17.9, 17.5, 18.1, 18. , 17.6, 18. , 18.1, 17.3, 17.3, 16.5, 17. , 17.4, 16.8, 16.7, 17.4, 17.1, 16.7, 16.2, 16.1, 15.7, 15.5, 16.3, 16. , 16.4, 16.2, 15.4, 15. , 14.9, 15.1, 14.8, 14.8, 15. , 14.6, 15.4, 14.8, 15.4, 14.1, 14.4, 14.4, 14.3, 14.3, 13.1, 13.4, 12.5, 12.9, 12.9, 12.8, 13.2, 13.1, 13. , 13.3, 11.6, 11.8, 11.9, 11.7, 11.6, 12.4, 11.6, 11.9, 11.6, 11.7, 12. , 12. , 10.5, 11.2, 11.2, 10.8, 9.7, 10.3, 10. , 9.7, 9.7, 9.5, 8.6, 8.5, 9.1, 9.1, 8.3, 7.7, 7.9, 7.6, 7.8, 6.7, 6.6, 7. , 7.1, 7.3, 6.8, 5.3, 4.2, 4.2, 4. ], dtype=float32) - satellite_img1(mid_date)object'7' '7' '7' '7' ... '7' '7' '7' '7'
- description :
- id of the satellite that acquired image 1
- standard_name :
- image1_satellite
array(['7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', ... '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7'], dtype=object) - satellite_img2(mid_date)object'7' '7' '7' '7' ... '8' '8' '8' '8'
- description :
- id of the satellite that acquired image 2
- standard_name :
- image2_satellite
array(['7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', '7', ... '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8', '8'], dtype=object) - sensor_img1(mid_date)object'E' 'E' 'E' 'E' ... 'E' 'E' 'E' 'E'
- description :
- id of the sensor that acquired image 1
- standard_name :
- image1_sensor
array(['E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', ... 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E'], dtype=object) - sensor_img2(mid_date)object'E' 'E' 'E' 'E' ... 'C' 'C' 'C' 'C'
- description :
- id of the sensor that acquired image 2
- standard_name :
- image2_sensor
array(['E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', 'E', ... 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C'], dtype=object) - stable_count_slow(mid_date)float643.802e+04 2.033e+04 ... 6.346e+03
- description :
- number of valid pixels over slowest 25% of ice
- standard_name :
- stable_count_slow
- units :
- count
array([3.8018e+04, 2.0331e+04, 5.2489e+04, 2.6288e+04, 3.2230e+03, 4.4707e+04, 5.9524e+04, 1.6033e+04, 2.1043e+04, 5.4368e+04, 6.2278e+04, 3.1265e+04, 2.1090e+03, 3.5488e+04, 1.7923e+04, 5.7940e+03, 2.7383e+04, 3.7733e+04, 9.5840e+03, 2.5190e+03, 5.7098e+04, 1.0614e+04, 1.5495e+04, 4.0829e+04, 1.4242e+04, 8.8150e+03, 4.7413e+04, 7.4510e+03, 7.7120e+03, 3.0770e+03, 1.0524e+04, 3.3036e+04, 3.4097e+04, 2.1750e+04, 3.2282e+04, 1.1280e+04, 1.3278e+04, 4.4867e+04, 3.7480e+04, 2.4021e+04, 3.3542e+04, 3.4385e+04, 4.0720e+03, 2.4631e+04, 2.3029e+04, 5.3053e+04, 3.0164e+04, 5.7390e+04, 5.7524e+04, 4.9046e+04, 2.2190e+04, 5.9630e+03, 4.6209e+04, 9.7160e+03, 6.0096e+04, 4.0572e+04, 1.6664e+04, 3.7350e+04, 4.1601e+04, 3.2830e+04, 2.1678e+04, 3.3420e+04, 5.7304e+04, 3.6253e+04, 3.0926e+04, 3.3518e+04, 4.9318e+04, 4.5330e+03, 3.7044e+04, 1.4253e+04, 3.6233e+04, 5.7814e+04, 1.1364e+04, 4.5145e+04, 1.8408e+04, 2.1000e+01, 6.0386e+04, 5.1242e+04, 6.4300e+02, 4.0676e+04, 6.0145e+04, 6.3993e+04, 3.2696e+04, 3.6250e+04, 5.9686e+04, 3.6459e+04, 1.1738e+04, 5.2623e+04, 1.8669e+04, 6.2392e+04, 3.1270e+04, 4.1567e+04, 2.0253e+04, 1.7058e+04, 1.3698e+04, 3.3642e+04, 1.1730e+04, 1.8364e+04, 4.6294e+04, 5.8840e+04, ... 6.2411e+04, 4.4160e+03, 5.0384e+04, 3.6351e+04, 5.9578e+04, 5.7183e+04, 5.5855e+04, 4.9174e+04, 5.3414e+04, 5.7930e+04, 5.9704e+04, 6.2705e+04, 5.9756e+04, 4.6269e+04, 4.6784e+04, 2.9542e+04, 4.6035e+04, 4.7483e+04, 4.0115e+04, 3.8341e+04, 4.8432e+04, 4.7527e+04, 4.0654e+04, 2.9060e+04, 2.3929e+04, 2.0455e+04, 1.5650e+04, 3.3103e+04, 5.3704e+04, 2.3565e+04, 1.9950e+04, 1.6876e+04, 6.2860e+03, 6.7550e+03, 8.3830e+03, 7.2160e+03, 6.2980e+03, 1.3660e+04, 1.4030e+03, 1.8022e+04, 7.8700e+03, 1.5509e+04, 4.7518e+04, 6.3114e+04, 4.2455e+04, 6.1610e+04, 6.1194e+04, 4.2007e+04, 3.9232e+04, 1.6166e+04, 3.8328e+04, 3.7879e+04, 2.4926e+04, 2.7073e+04, 4.0076e+04, 4.7231e+04, 4.5839e+04, 1.2114e+04, 1.4474e+04, 1.7988e+04, 1.2946e+04, 9.6390e+03, 1.8005e+04, 1.4396e+04, 1.8290e+04, 1.2845e+04, 6.1057e+04, 2.1392e+04, 2.2063e+04, 5.8312e+04, 6.8130e+03, 7.1130e+03, 5.8325e+04, 4.3602e+04, 5.4960e+04, 5.0288e+04, 4.3470e+04, 4.5534e+04, 4.1324e+04, 2.5098e+04, 2.1837e+04, 3.3971e+04, 3.4213e+04, 6.6450e+03, 7.8180e+03, 1.1407e+04, 5.6180e+03, 9.6200e+03, 5.5864e+04, 5.5243e+04, 6.1718e+04, 6.2764e+04, 1.5400e+03, 5.7479e+04, 3.0412e+04, 1.0553e+04, 1.1070e+04, 6.3460e+03]) - stable_count_stationary(mid_date)float643.752e+04 1.859e+04 ... 6.286e+03
- description :
- number of valid pixels over stationary or slow-flowing surfaces
- standard_name :
- stable_count_stationary
- units :
- count
array([3.7524e+04, 1.8587e+04, 5.0980e+04, 2.5880e+04, 3.7800e+02, 4.0116e+04, 5.7789e+04, 1.1539e+04, 9.0090e+03, 5.3881e+04, 6.1167e+04, 2.9141e+04, 1.3660e+03, 3.5017e+04, 8.1260e+03, 5.3380e+03, 2.5441e+04, 2.8178e+04, 9.0960e+03, 5.6059e+04, 5.6273e+04, 7.6850e+03, 1.3577e+04, 3.0771e+04, 1.2301e+04, 1.1750e+03, 4.3211e+04, 3.0060e+03, 7.4720e+03, 6.1073e+04, 4.6020e+03, 3.2760e+04, 2.9293e+04, 1.5430e+04, 2.6003e+04, 1.0944e+04, 1.2148e+04, 4.4695e+04, 3.7248e+04, 2.3177e+04, 3.0481e+04, 2.5554e+04, 3.9550e+03, 2.3269e+04, 1.9987e+04, 4.5969e+04, 3.0044e+04, 4.9129e+04, 5.5879e+04, 3.9283e+04, 1.2834e+04, 3.5190e+03, 4.5409e+04, 6.5029e+04, 5.7348e+04, 3.2184e+04, 1.6238e+04, 3.5154e+04, 3.7118e+04, 2.7076e+04, 2.0648e+04, 3.2870e+04, 5.4484e+04, 3.4505e+04, 2.7001e+04, 2.3039e+04, 4.2729e+04, 3.3970e+03, 3.5217e+04, 1.0290e+04, 3.5508e+04, 5.2066e+04, 1.0720e+04, 4.4141e+04, 1.3354e+04, 6.2799e+04, 5.9246e+04, 4.9018e+04, 6.2000e+02, 3.4709e+04, 5.7535e+04, 5.6074e+04, 2.9412e+04, 3.6016e+04, 5.9378e+04, 3.4328e+04, 1.1026e+04, 5.2061e+04, 1.7635e+04, 6.2366e+04, 2.9936e+04, 3.7663e+04, 1.7687e+04, 1.1678e+04, 1.1549e+04, 3.1640e+04, 1.1249e+04, 1.6980e+04, 4.5611e+04, 5.8624e+04, ... 6.0729e+04, 3.3070e+03, 4.7883e+04, 3.4175e+04, 5.8006e+04, 5.6205e+04, 5.4223e+04, 4.5596e+04, 5.0555e+04, 5.6810e+04, 5.8648e+04, 6.0813e+04, 5.5916e+04, 4.4657e+04, 4.5213e+04, 2.8631e+04, 4.5407e+04, 4.6397e+04, 3.9106e+04, 3.7637e+04, 4.7636e+04, 4.6582e+04, 3.9850e+04, 2.8342e+04, 2.0434e+04, 1.9477e+04, 1.3444e+04, 3.1433e+04, 5.3094e+04, 2.2138e+04, 1.8980e+04, 1.4937e+04, 3.7000e+03, 4.4940e+03, 5.8850e+03, 6.5660e+03, 4.3700e+03, 1.3177e+04, 6.5271e+04, 1.5967e+04, 5.7320e+03, 1.2926e+04, 4.5380e+04, 6.2415e+04, 4.1239e+04, 6.0898e+04, 5.9384e+04, 4.0756e+04, 3.7220e+04, 1.4939e+04, 3.7610e+04, 3.7456e+04, 2.3550e+04, 2.5851e+04, 3.8176e+04, 4.6726e+04, 4.4344e+04, 1.1420e+04, 1.3045e+04, 1.7446e+04, 1.2535e+04, 8.8420e+03, 1.7416e+04, 1.2945e+04, 1.7998e+04, 1.1719e+04, 5.9637e+04, 2.0988e+04, 2.1044e+04, 5.7072e+04, 6.2170e+03, 6.2230e+03, 5.7669e+04, 4.3146e+04, 5.4532e+04, 4.9204e+04, 4.3000e+04, 4.5264e+04, 4.1019e+04, 2.4682e+04, 2.1207e+04, 3.2929e+04, 3.3766e+04, 6.1770e+03, 7.3360e+03, 1.0623e+04, 3.0560e+03, 8.9140e+03, 5.5392e+04, 5.4762e+04, 6.1172e+04, 6.2270e+04, 1.3030e+03, 5.7246e+04, 3.0096e+04, 1.0239e+04, 1.0862e+04, 6.2860e+03]) - stable_shift_flag(mid_date)float641.0 1.0 1.0 1.0 ... 1.0 1.0 1.0 1.0
- description :
- flag for applying velocity bias correction: 0 = no correction; 1 = correction from overlapping stable surface mask (stationary or slow-flowing surfaces with velocity < 15 m/yr)(top priority); 2 = correction from slowest 25% of overlapping velocities (second priority)
- standard_name :
- stable_shift_flag
array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., ... 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.]) - v(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity magnitude
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_velocity
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - v_error(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity magnitude error
- grid_mapping :
- mapping
- standard_name :
- velocity_error
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - va(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity in radar azimuth direction
- grid_mapping :
- mapping
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - va_error(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- error for velocity in radar azimuth direction
- standard_name :
- va_error
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - va_error_modeled(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- va_error_modeled
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - va_error_slow(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- va_error_slow
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - va_error_stationary(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- va_error_stationary
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - va_stable_shift(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- applied va shift calibrated using pixels over stable or slow surfaces
- standard_name :
- va_stable_shift
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - va_stable_shift_slow(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- va shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- va_stable_shift_slow
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - va_stable_shift_stationary(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- va shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- va_stable_shift_stationary
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vr(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity in radar range direction
- grid_mapping :
- mapping
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - vr_error(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- error for velocity in radar range direction
- standard_name :
- vr_error
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vr_error_modeled(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vr_error_modeled
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vr_error_slow(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vr_error_slow
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vr_error_stationary(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vr_error_stationary
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vr_stable_shift(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- applied vr shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vr_stable_shift
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vr_stable_shift_slow(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- vr shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vr_stable_shift_slow
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vr_stable_shift_stationary(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- vr shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vr_stable_shift_stationary
- units :
- meter/year
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, ... nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - vx(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity component in x direction
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_x_velocity
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - vx_error(mid_date)float326.3 6.6 3.8 8.4 ... 23.3 17.9 11.7
- description :
- best estimate of x_velocity error: vx_error is populated according to the approach used for the velocity bias correction as indicated in "stable_shift_flag"
- standard_name :
- vx_error
- units :
- meter/year
array([ 6.3, 6.6, 3.8, 8.4, 20.5, 6.3, 11.8, 3.7, 72.4, 3.6, 11.9, 6.1, 5.1, 25.7, 5.5, 6.3, 51.9, 4.3, 5.6, 50.8, 11.1, 43. , 10.3, 4.9, 5.6, 27.2, 26.8, 3.6, 12.8, 39.7, 4.9, 24.5, 8.6, 16.3, 4.7, 49.6, 10.5, 5.9, 4.2, 15.1, 56. , 7.4, 3.4, 8.5, 6.8, 5.1, 3.9, 7.2, 17.9, 45.3, 4.8, 38.6, 50.4, 112.3, 10.7, 5.7, 6. , 6.2, 48.1, 49.8, 4.8, 4. , 4.8, 9.1, 5.4, 4.6, 4.6, 3.7, 3.1, 12.1, 97.5, 8. , 12.1, 7.9, 33. , 7.1, 5.7, 3.4, 9.8, 6.7, 4.5, 4.3, 86. , 5.9, 3.9, 44.7, 43.6, 7.7, 12.2, 6.4, 5.1, 30.3, 9.1, 48.3, 4.2, 14.8, 51.1, 5.3, 41.9, 9.8, 7.4, 5.9, 5.9, 4.4, 4.6, 5.5, 3.4, 10.5, 30.3, 39.8, 35.7, 8. , 12.4, 4. , 5.5, 4.9, 9.1, 7.3, 183.1, 111.7, 31.7, 9.3, 16.4, 3.8, 7.7, 8.1, 5.9, 3.1, 4.5, 4.5, 6.9, 8. , 5. , 82.9, 18.5, 4.4, 51.5, 35.3, 6.9, 229.5, 4.8, 10.3, 7.2, 31.9, 4.2, 5.8, 10.3, 4.7, 4.2, 4.2, 7.8, 16. , 28.7, 6.4, 19.9, 13.2, 6. , 17.4, 20.4, 8.7, 48.3, 5.5, 6.9, 7.2, 3.3, 25.5, 12.2, 7.7, 3.3, 14.9, 22.8, 6.3, 5.9, 6.2, 98. , 17.1, 5.8, 29.3, 18. , 42.7, ... 7. , 4.5, 5.2, 5.1, 33.6, 122.5, 166.8, 9.2, 7.8, 140.2, 12.9, 7.9, 16.5, 27.2, 4.5, 9.4, 16.6, 90.5, 29.7, 6. , 7.1, 8.7, 10.6, 7.3, 6.3, 5.1, 61.2, 48.7, 4.5, 20.8, 5.6, 19.2, 5. , 6.2, 17.4, 7.4, 8. , 6.7, 10.4, 16.5, 19.8, 7.7, 17.4, 16. , 4.7, 11.2, 4.3, 11.6, 8.8, 305.9, 10.5, 10.5, 5.3, 5.6, 9.5, 38.5, 18.2, 11.4, 5.4, 20.3, 5.2, 10.5, 7.9, 9.1, 13.5, 15.4, 18.2, 13.5, 58.7, 17.8, 15.2, 6.2, 6.1, 13.6, 13.1, 12.9, 11.8, 9.3, 5.8, 24.7, 4.4, 44.8, 19.8, 11.1, 9.6, 11.6, 11.9, 25.3, 4.4, 5.5, 56.2, 11.5, 20.4, 20. , 8.4, 5.4, 18.1, 12.7, 13.7, 14.1, 8.1, 11.6, 7.8, 12.9, 18.6, 7.5, 16.3, 11.5, 13. , 9.1, 19.3, 23. , 9.4, 18.3, 59. , 5.4, 13.9, 13.7, 4.1, 9.4, 8.5, 6.9, 75.7, 9.6, 34.9, 8.9, 17.4, 33.8, 5.1, 19.8, 23.2, 10.5, 54.1, 13.1, 10.7, 5. , 14.4, 5. , 56.4, 18.5, 3.6, 5.3, 7.3, 80.4, 19.9, 15.2, 5.4, 6.1, 24.3, 7.1, 32.7, 10.2, 29.5, 598.8, 11.6, 35.7, 15.1, 35.3, 7.6, 23. , 22.9, 109.1, 18.9, 11.2, 25.1, 37.1, 8.2, 19.7, 25.8, 10.7, 23.3, 17.9, 11.7], dtype=float32) - vx_error_modeled(mid_date)float3224.2 24.2 21.5 ... 89.5 46.5 46.5
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vx_error_modeled
- units :
- meter/year
array([ 24.2, 24.2, 21.5, 34.2, 83.1, 23.3, 38.8, 24.2, 290.9, 19.4, 58.2, 29.1, 27.7, 145.4, 27.7, 38.8, 290.9, 21.5, 36.4, 290.9, 58.2, 193.9, 48.5, 26.4, 27.7, 145.4, 145.4, 20.8, 48.5, 193.9, 21.5, 145.4, 30.6, 83.1, 25.3, 290.9, 34.2, 26.4, 27.7, 83.1, 290.9, 29.1, 18.2, 32.3, 29.1, 25.3, 22.4, 27.7, 72.7, 290.9, 24.2, 145.4, 193.9, 581.7, 27.7, 29.1, 24.2, 27.7, 290.9, 290.9, 18.8, 20.8, 25.3, 32.3, 21.5, 23.3, 22.4, 17.1, 17.1, 36.4, 290.9, 26.4, 36.4, 29.1, 145.4, 32.3, 20.1, 20.1, 38.8, 23.3, 20.8, 24.2, 193.9, 18.8, 18.2, 193.9, 145.4, 41.6, 72.7, 30.6, 23.3, 145.4, 38.8, 145.4, 23.3, 83.1, 290.9, 19.4, 193.9, 44.7, 38.8, 26.4, 23.3, 17.1, 24.2, 29.1, 19.4, 38.8, 116.3, 193.9, 116.3, 25.3, 41.6, 17.1, 23.3, 21.5, 32.3, 34.2, 581.7, 581.7, 145.4, 36.4, 83.1, 17.1, 30.6, 38.8, 20.8, 19.4, 20.1, 20.8, 26.4, 29.1, 27.7, 581.7, 64.6, 20.1, 193.9, 145.4, 29.1, 581.7, 24.2, 44.7, 32.3, 97. , 20.8, 30.6, 44.7, 22.4, 23.3, 20.8, 32.3, 58.2, 145.4, 30.6, 52.9, 83.1, 30.6, 72.7, 52.9, 27.7, ... 89.5, 22.8, 22. , 25.9, 24.8, 22.8, 21.2, 21.2, 232.7, 129.3, 17.4, 68.4, 28.4, 50.6, 22.8, 22. , 29.8, 25.9, 25.9, 20.4, 37.5, 37.5, 46.5, 20.4, 46.5, 35.3, 20.4, 19.1, 22.8, 33.2, 21.2, 1163.6, 22.8, 23.7, 20.4, 18.5, 31.4, 129.3, 43.1, 40.1, 24.8, 68.4, 28.4, 21.2, 24.8, 22. , 50.6, 50.6, 33.2, 46.5, 166.2, 40.1, 35.3, 19.7, 21.2, 31.4, 46.5, 43.1, 19.7, 37.5, 27.1, 77.6, 19.7, 129.3, 68.4, 40.1, 31.4, 25.9, 40.1, 77.6, 19.7, 19.7, 232.7, 37.5, 55.4, 77.6, 28.4, 18.5, 43.1, 29.8, 23.7, 61.2, 29.8, 28.4, 23.7, 43.1, 50.6, 25.9, 61.2, 29.8, 33.2, 35.3, 46.5, 89.5, 50.6, 61.2, 129.3, 19.7, 35.3, 43.1, 21.2, 31.4, 22. , 25.9, 166.2, 28.4, 166.2, 18.5, 61.2, 89.5, 27.1, 55.4, 55.4, 27.1, 166.2, 31.4, 25.9, 17.9, 77.6, 23.7, 105.8, 37.5, 17.4, 25.9, 31.4, 387.8, 50.6, 33.2, 19.1, 22.8, 68.4, 17.4, 105.8, 35.3, 68.4, 1163.7, 28.4, 166.2, 55.4, 89.5, 29.8, 50.6, 55.4, 387.8, 50.6, 68.4, 77.6, 105.8, 33.2, 55.4, 61.2, 37.5, 89.5, 46.5, 46.5], dtype=float32) - vx_error_slow(mid_date)float326.3 6.6 3.8 8.4 ... 23.3 17.9 11.6
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vx_error_slow
- units :
- meter/year
array([ 6.3, 6.6, 3.8, 8.4, 20.5, 6.3, 11.8, 3.7, 72.4, 3.6, 11.9, 6.1, 5.1, 25.7, 5.5, 6.3, 51.9, 4.3, 5.6, 50.8, 11.1, 43. , 10.3, 4.9, 5.6, 27.2, 26.8, 3.6, 12.8, 39.7, 4.9, 24.5, 8.6, 16.3, 4.7, 49.6, 10.5, 5.9, 4.2, 15.1, 56. , 7.4, 3.4, 8.5, 6.8, 5.1, 3.9, 7.2, 17.8, 45.3, 4.8, 38.5, 50.4, 112.2, 10.7, 5.7, 6. , 6.2, 48.1, 49.8, 4.8, 4. , 4.8, 9.1, 5.4, 4.6, 4.6, 3.7, 3.1, 12.1, 97.4, 8. , 12.1, 7.8, 33. , 7.1, 5.7, 3.4, 9.8, 6.7, 4.5, 4.3, 85.8, 5.9, 3.9, 44.7, 43.6, 7.7, 12.2, 6.4, 5.1, 30.3, 9.1, 48.2, 4.2, 14.8, 51.1, 5.3, 41.9, 9.8, 7.4, 5.9, 5.9, 4.4, 4.6, 5.5, 3.4, 10.5, 30.3, 39.7, 35.7, 8. , 12.4, 4. , 5.5, 4.9, 9.1, 7.3, 183.2, 111.7, 31.7, 9.3, 16.4, 3.8, 7.7, 8.1, 5.9, 3.1, 4.5, 4.5, 6.9, 8. , 5. , 83.1, 18.5, 4.4, 51.4, 35.3, 6.9, 229.4, 4.8, 10.3, 7.2, 31.8, 4.2, 5.8, 10.3, 4.7, 4.2, 4.2, 7.8, 16. , 28.7, 6.4, 19.9, 13.2, 6. , 17.4, 20.4, 8.7, 48.3, 5.5, 6.9, 7.2, 3.3, 25.4, 12.2, 7.7, 3.3, 14.9, 22.8, 6.3, 5.9, 6.2, 98.2, 17. , 5.7, 29.3, 18. , 42.7, ... 7. , 4.5, 5.2, 5.1, 33.5, 122.5, 166.7, 9.2, 7.8, 140. , 12.9, 7.9, 16.5, 27.1, 4.5, 9.4, 16.6, 90.5, 29.7, 6. , 7.1, 8.7, 10.6, 7.3, 6.3, 5.1, 61. , 48.7, 4.5, 20.8, 5.6, 19.2, 5.1, 6.2, 17.3, 7.4, 8. , 6.7, 10.4, 16.5, 19.8, 7.7, 17.4, 16. , 4.7, 11.2, 4.3, 11.6, 8.8, 305.9, 10.5, 10.5, 5.2, 5.6, 9.5, 38.5, 18.2, 11.4, 5.4, 20.3, 5.2, 10.5, 7.9, 9.1, 13.5, 15.4, 18.2, 13.5, 58.6, 17.8, 15.1, 6.2, 6.1, 13.6, 13.1, 12.9, 11.8, 9.3, 5.8, 24.7, 4.4, 44.7, 19.7, 11.1, 9.6, 11.6, 11.9, 25.2, 4.4, 5.5, 56.2, 11.5, 20.3, 20. , 8.4, 5.4, 18.1, 12.7, 13.7, 14. , 8.1, 11.5, 7.7, 12.9, 18.6, 7.5, 16.3, 11.4, 12.9, 9.1, 19.3, 23. , 9.4, 18.3, 59. , 5.3, 13.8, 13.7, 4.1, 9.4, 8.5, 6.9, 75.6, 9.5, 34.9, 8.9, 17.4, 33.8, 5.1, 19.8, 23.1, 10.5, 54.1, 13.1, 10.7, 5. , 14.4, 5. , 56.3, 18.5, 3.6, 5.3, 7.3, 80.3, 19.9, 15.2, 5.4, 6.1, 24.3, 7.1, 32.7, 10.1, 29.5, 598.5, 11.6, 35.7, 15. , 35.3, 7.6, 23. , 22.9, 108.5, 18.9, 11.2, 25.1, 37. , 8.2, 19.7, 25.9, 10.7, 23.3, 17.9, 11.6], dtype=float32) - vx_error_stationary(mid_date)float326.3 6.6 3.8 8.4 ... 23.3 17.9 11.7
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 meter/year identified from an external mask
- standard_name :
- vx_error_stationary
- units :
- meter/year
array([ 6.3, 6.6, 3.8, 8.4, 20.5, 6.3, 11.8, 3.7, 72.4, 3.6, 11.9, 6.1, 5.1, 25.7, 5.5, 6.3, 51.9, 4.3, 5.6, 50.8, 11.1, 43. , 10.3, 4.9, 5.6, 27.2, 26.8, 3.6, 12.8, 39.7, 4.9, 24.5, 8.6, 16.3, 4.7, 49.6, 10.5, 5.9, 4.2, 15.1, 56. , 7.4, 3.4, 8.5, 6.8, 5.1, 3.9, 7.2, 17.9, 45.3, 4.8, 38.6, 50.4, 112.3, 10.7, 5.7, 6. , 6.2, 48.1, 49.8, 4.8, 4. , 4.8, 9.1, 5.4, 4.6, 4.6, 3.7, 3.1, 12.1, 97.5, 8. , 12.1, 7.9, 33. , 7.1, 5.7, 3.4, 9.8, 6.7, 4.5, 4.3, 86. , 5.9, 3.9, 44.7, 43.6, 7.7, 12.2, 6.4, 5.1, 30.3, 9.1, 48.3, 4.2, 14.8, 51.1, 5.3, 41.9, 9.8, 7.4, 5.9, 5.9, 4.4, 4.6, 5.5, 3.4, 10.5, 30.3, 39.8, 35.7, 8. , 12.4, 4. , 5.5, 4.9, 9.1, 7.3, 183.1, 111.7, 31.7, 9.3, 16.4, 3.8, 7.7, 8.1, 5.9, 3.1, 4.5, 4.5, 6.9, 8. , 5. , 82.9, 18.5, 4.4, 51.5, 35.3, 6.9, 229.5, 4.8, 10.3, 7.2, 31.9, 4.2, 5.8, 10.3, 4.7, 4.2, 4.2, 7.8, 16. , 28.7, 6.4, 19.9, 13.2, 6. , 17.4, 20.4, 8.7, 48.3, 5.5, 6.9, 7.2, 3.3, 25.5, 12.2, 7.7, 3.3, 14.9, 22.8, 6.3, 5.9, 6.2, 98. , 17.1, 5.8, 29.3, 18. , 42.7, ... 7. , 4.5, 5.2, 5.1, 33.6, 122.5, 166.8, 9.2, 7.8, 140.2, 12.9, 7.9, 16.5, 27.2, 4.5, 9.4, 16.6, 90.5, 29.7, 6. , 7.1, 8.7, 10.6, 7.3, 6.3, 5.1, 61.2, 48.7, 4.5, 20.8, 5.6, 19.2, 5. , 6.2, 17.4, 7.4, 8. , 6.7, 10.4, 16.5, 19.8, 7.7, 17.4, 16. , 4.7, 11.2, 4.3, 11.6, 8.8, 305.9, 10.5, 10.5, 5.3, 5.6, 9.5, 38.5, 18.2, 11.4, 5.4, 20.3, 5.2, 10.5, 7.9, 9.1, 13.5, 15.4, 18.2, 13.5, 58.7, 17.8, 15.2, 6.2, 6.1, 13.6, 13.1, 12.9, 11.8, 9.3, 5.8, 24.7, 4.4, 44.8, 19.8, 11.1, 9.6, 11.6, 11.9, 25.3, 4.4, 5.5, 56.2, 11.5, 20.4, 20. , 8.4, 5.4, 18.1, 12.7, 13.7, 14.1, 8.1, 11.6, 7.8, 12.9, 18.6, 7.5, 16.3, 11.5, 13. , 9.1, 19.3, 23. , 9.4, 18.3, 59. , 5.4, 13.9, 13.7, 4.1, 9.4, 8.5, 6.9, 75.7, 9.6, 34.9, 8.9, 17.4, 33.8, 5.1, 19.8, 23.2, 10.5, 54.1, 13.1, 10.7, 5. , 14.4, 5. , 56.4, 18.5, 3.6, 5.3, 7.3, 80.4, 19.9, 15.2, 5.4, 6.1, 24.3, 7.1, 32.7, 10.2, 29.5, 598.8, 11.6, 35.7, 15.1, 35.3, 7.6, 23. , 22.9, 109.1, 18.9, 11.2, 25.1, 37.1, 8.2, 19.7, 25.8, 10.7, 23.3, 17.9, 11.7], dtype=float32) - vx_stable_shift(mid_date)float320.5 -1.1 0.4 ... -12.0 -24.3 -0.3
- description :
- applied vx shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vx_stable_shift
- units :
- meter/year
array([ 5.000e-01, -1.100e+00, 4.000e-01, -5.200e+00, 6.700e+00, -1.100e+00, -2.000e+00, 1.800e+00, 1.070e+01, -7.000e-01, -1.400e+00, 2.700e+00, -1.000e+00, 2.560e+01, -1.000e-01, 8.000e-01, -1.110e+01, 2.200e+00, 4.000e-01, 1.420e+01, 4.000e-01, 1.430e+01, 3.000e+00, 0.000e+00, 4.100e+00, 9.900e+00, -2.500e+00, 7.000e-01, 4.100e+00, 3.400e+01, 6.000e-01, -2.980e+01, 2.400e+00, 1.390e+01, 0.000e+00, 6.000e+00, -3.100e+00, -5.200e+00, 4.400e+00, 4.100e+00, -2.700e+00, 2.100e+00, -2.200e+00, -3.400e+00, -2.200e+00, 2.000e+00, 3.300e+00, 0.000e+00, 5.500e+00, 1.720e+01, 3.600e+00, 6.000e+00, 1.290e+01, 8.200e+00, 6.800e+00, 8.000e-01, 2.300e+00, -1.600e+00, -2.140e+01, 9.500e+00, -1.100e+00, -1.000e+00, 5.500e+00, -2.400e+00, -1.000e-01, -1.000e+00, 3.000e-01, 2.500e+00, 1.300e+00, -2.000e+00, 1.590e+01, 1.100e+00, 1.200e+00, -5.100e+00, 3.400e+00, -1.600e+00, -1.400e+00, -9.000e-01, 5.800e+00, 1.000e-01, 8.000e-01, -8.000e-01, -2.440e+01, -9.000e-01, 1.200e+00, -1.460e+01, 1.000e+00, 2.100e+00, 3.600e+00, 5.200e+00, 1.300e+00, 5.300e+00, -2.000e+00, 2.100e+00, 4.000e-01, 4.900e+00, -3.360e+01, 6.000e-01, 3.580e+01, 7.000e-01, ... -1.600e+00, -7.100e+00, -1.400e+00, -4.800e+00, -1.900e+00, -7.000e-01, -2.600e+00, 0.000e+00, -2.500e+00, -1.500e+00, -7.600e+00, 5.000e-01, -1.800e+00, 1.400e+00, -3.600e+00, 7.700e+00, -1.400e+00, -3.200e+00, -5.300e+00, -6.300e+00, -1.600e+00, -1.110e+01, -6.700e+00, -2.600e+00, 2.300e+00, -1.000e+00, 0.000e+00, -1.100e+00, -1.230e+01, -9.700e+00, -4.800e+00, -6.500e+00, 1.700e+00, 5.000e-01, 1.300e+00, -1.820e+01, -7.300e+00, -1.080e+01, -1.080e+01, -2.390e+01, -2.900e+00, 6.000e-01, -4.700e+00, -3.300e+00, -4.500e+00, -5.400e+00, -7.000e-01, -2.910e+01, 3.000e-01, 5.700e+00, -5.700e+00, -1.130e+01, -1.090e+01, 3.000e-01, 1.000e-01, -2.110e+01, -3.100e+00, -1.650e+01, 0.000e+00, -1.010e+01, -4.000e+00, -1.470e+01, -1.000e+00, -9.300e+00, -1.490e+01, 4.000e-01, -6.200e+00, -3.800e+00, -6.320e+01, 1.000e-01, -7.300e+00, -1.400e+00, -4.300e+00, -2.400e+00, -2.500e+00, -1.560e+01, -6.500e+00, -2.660e+01, 1.770e+01, -4.200e+00, -1.020e+01, -1.170e+01, -3.370e+01, -5.500e+00, -1.550e+01, 2.800e+00, 1.370e+01, -5.700e+00, -1.440e+01, -3.140e+01, -1.170e+01, -7.100e+00, -7.400e+00, -3.900e+00, -5.600e+00, -1.200e+01, -2.430e+01, -3.000e-01], dtype=float32) - vx_stable_shift_slow(mid_date)float320.5 -1.1 0.4 ... -12.1 -24.3 -0.2
- description :
- vx shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vx_stable_shift_slow
- units :
- meter/year
array([ 5.000e-01, -1.100e+00, 4.000e-01, -5.200e+00, 6.800e+00, -1.200e+00, -2.000e+00, 1.800e+00, 1.070e+01, -7.000e-01, -1.400e+00, 2.700e+00, -1.000e+00, 2.560e+01, -1.000e-01, 8.000e-01, -1.100e+01, 2.200e+00, 4.000e-01, 1.400e+01, 4.000e-01, 1.430e+01, 3.000e+00, 0.000e+00, 4.100e+00, 1.000e+01, -2.500e+00, 7.000e-01, 4.100e+00, 3.400e+01, 6.000e-01, -2.970e+01, 2.400e+00, 1.400e+01, 0.000e+00, 5.900e+00, -3.200e+00, -5.200e+00, 4.400e+00, 4.100e+00, -2.600e+00, 2.100e+00, -2.200e+00, -3.400e+00, -2.200e+00, 2.000e+00, 3.300e+00, 0.000e+00, 5.600e+00, 1.720e+01, 3.600e+00, 6.000e+00, 1.280e+01, 8.200e+00, 6.800e+00, 8.000e-01, 2.300e+00, -1.600e+00, -2.140e+01, 9.500e+00, -1.100e+00, -1.000e+00, 5.400e+00, -2.400e+00, -1.000e-01, -9.000e-01, 3.000e-01, 2.500e+00, 1.300e+00, -2.100e+00, 1.580e+01, 1.100e+00, 1.200e+00, -5.100e+00, 3.400e+00, -1.600e+00, -1.400e+00, -9.000e-01, 5.900e+00, 1.000e-01, 8.000e-01, -8.000e-01, -2.440e+01, -9.000e-01, 1.200e+00, -1.450e+01, 9.000e-01, 2.100e+00, 3.600e+00, 5.200e+00, 1.300e+00, 5.300e+00, -2.000e+00, 1.900e+00, 4.000e-01, 5.000e+00, -3.360e+01, 6.000e-01, 3.560e+01, 7.000e-01, ... -1.600e+00, -7.100e+00, -1.400e+00, -4.800e+00, -1.900e+00, -7.000e-01, -2.600e+00, 0.000e+00, -2.500e+00, -1.500e+00, -7.600e+00, 5.000e-01, -1.900e+00, 1.400e+00, -3.600e+00, 7.600e+00, -1.400e+00, -3.300e+00, -5.300e+00, -6.300e+00, -1.600e+00, -1.110e+01, -6.700e+00, -2.600e+00, 2.300e+00, -1.000e+00, 0.000e+00, -1.100e+00, -1.230e+01, -9.600e+00, -4.700e+00, -6.500e+00, 1.700e+00, 5.000e-01, 1.300e+00, -1.820e+01, -7.200e+00, -1.080e+01, -1.080e+01, -2.380e+01, -2.900e+00, 7.000e-01, -4.700e+00, -3.300e+00, -4.500e+00, -5.400e+00, -7.000e-01, -2.840e+01, 3.000e-01, 5.500e+00, -5.700e+00, -1.130e+01, -1.070e+01, 3.000e-01, 1.000e-01, -2.100e+01, -3.100e+00, -1.650e+01, 0.000e+00, -1.010e+01, -4.000e+00, -1.470e+01, -1.000e+00, -9.400e+00, -1.490e+01, 4.000e-01, -6.100e+00, -3.800e+00, -6.310e+01, 1.000e-01, -7.300e+00, -1.400e+00, -4.300e+00, -2.400e+00, -2.500e+00, -1.560e+01, -6.500e+00, -2.660e+01, 1.840e+01, -4.200e+00, -1.030e+01, -1.170e+01, -3.370e+01, -5.500e+00, -1.550e+01, 2.800e+00, 1.420e+01, -5.600e+00, -1.440e+01, -3.140e+01, -1.170e+01, -7.100e+00, -7.300e+00, -3.800e+00, -5.600e+00, -1.210e+01, -2.430e+01, -2.000e-01], dtype=float32) - vx_stable_shift_stationary(mid_date)float320.5 -1.1 0.4 ... -12.0 -24.3 -0.3
- description :
- vx shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vx_stable_shift_stationary
- units :
- meter/year
array([ 5.000e-01, -1.100e+00, 4.000e-01, -5.200e+00, 6.700e+00, -1.100e+00, -2.000e+00, 1.800e+00, 1.070e+01, -7.000e-01, -1.400e+00, 2.700e+00, -1.000e+00, 2.560e+01, -1.000e-01, 8.000e-01, -1.110e+01, 2.200e+00, 4.000e-01, 1.420e+01, 4.000e-01, 1.430e+01, 3.000e+00, 0.000e+00, 4.100e+00, 9.900e+00, -2.500e+00, 7.000e-01, 4.100e+00, 3.400e+01, 6.000e-01, -2.980e+01, 2.400e+00, 1.390e+01, 0.000e+00, 6.000e+00, -3.100e+00, -5.200e+00, 4.400e+00, 4.100e+00, -2.700e+00, 2.100e+00, -2.200e+00, -3.400e+00, -2.200e+00, 2.000e+00, 3.300e+00, 0.000e+00, 5.500e+00, 1.720e+01, 3.600e+00, 6.000e+00, 1.290e+01, 8.200e+00, 6.800e+00, 8.000e-01, 2.300e+00, -1.600e+00, -2.140e+01, 9.500e+00, -1.100e+00, -1.000e+00, 5.500e+00, -2.400e+00, -1.000e-01, -1.000e+00, 3.000e-01, 2.500e+00, 1.300e+00, -2.000e+00, 1.590e+01, 1.100e+00, 1.200e+00, -5.100e+00, 3.400e+00, -1.600e+00, -1.400e+00, -9.000e-01, 5.800e+00, 1.000e-01, 8.000e-01, -8.000e-01, -2.440e+01, -9.000e-01, 1.200e+00, -1.460e+01, 1.000e+00, 2.100e+00, 3.600e+00, 5.200e+00, 1.300e+00, 5.300e+00, -2.000e+00, 2.100e+00, 4.000e-01, 4.900e+00, -3.360e+01, 6.000e-01, 3.580e+01, 7.000e-01, ... -1.600e+00, -7.100e+00, -1.400e+00, -4.800e+00, -1.900e+00, -7.000e-01, -2.600e+00, 0.000e+00, -2.500e+00, -1.500e+00, -7.600e+00, 5.000e-01, -1.800e+00, 1.400e+00, -3.600e+00, 7.700e+00, -1.400e+00, -3.200e+00, -5.300e+00, -6.300e+00, -1.600e+00, -1.110e+01, -6.700e+00, -2.600e+00, 2.300e+00, -1.000e+00, 0.000e+00, -1.100e+00, -1.230e+01, -9.700e+00, -4.800e+00, -6.500e+00, 1.700e+00, 5.000e-01, 1.300e+00, -1.820e+01, -7.300e+00, -1.080e+01, -1.080e+01, -2.390e+01, -2.900e+00, 6.000e-01, -4.700e+00, -3.300e+00, -4.500e+00, -5.400e+00, -7.000e-01, -2.910e+01, 3.000e-01, 5.700e+00, -5.700e+00, -1.130e+01, -1.090e+01, 3.000e-01, 1.000e-01, -2.110e+01, -3.100e+00, -1.650e+01, 0.000e+00, -1.010e+01, -4.000e+00, -1.470e+01, -1.000e+00, -9.300e+00, -1.490e+01, 4.000e-01, -6.200e+00, -3.800e+00, -6.320e+01, 1.000e-01, -7.300e+00, -1.400e+00, -4.300e+00, -2.400e+00, -2.500e+00, -1.560e+01, -6.500e+00, -2.660e+01, 1.770e+01, -4.200e+00, -1.020e+01, -1.170e+01, -3.370e+01, -5.500e+00, -1.550e+01, 2.800e+00, 1.370e+01, -5.700e+00, -1.440e+01, -3.140e+01, -1.170e+01, -7.100e+00, -7.400e+00, -3.900e+00, -5.600e+00, -1.200e+01, -2.430e+01, -3.000e-01], dtype=float32) - vy(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity component in y direction
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_y_velocity
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - vy_error(mid_date)float324.3 5.0 3.4 6.3 ... 23.3 6.6 9.7
- description :
- best estimate of y_velocity error: vy_error is populated according to the approach used for the velocity bias correction as indicated in "stable_shift_flag"
- standard_name :
- vy_error
- units :
- meter/year
array([ 4.3, 5. , 3.4, 6.3, 19.5, 7.7, 7.6, 3.2, 109.7, 4. , 20.4, 7. , 4.1, 30.1, 5.4, 8.2, 60. , 4.1, 6.5, 43.1, 15. , 42.9, 9.5, 3.3, 5.7, 26. , 21.9, 4.1, 9.8, 37. , 3.7, 26.4, 6.7, 18.9, 4.2, 48.6, 7.2, 7.2, 4.4, 15.7, 47. , 4.3, 3.5, 10.2, 11.1, 6. , 5.4, 6.9, 18.6, 39.1, 4.5, 28.5, 33. , 163.6, 6. , 5.5, 5.2, 4.7, 34.3, 44. , 5. , 3.4, 5.2, 6.3, 3.9, 2.9, 5.4, 5.4, 3.4, 8. , 46. , 6.2, 7.3, 5.7, 24.9, 7.4, 4.9, 4.4, 11.9, 3.7, 5.1, 6.4, 35.8, 4.1, 4.8, 33.5, 28.7, 9.6, 14. , 4.6, 5.1, 22. , 7.7, 30.7, 4.1, 15.1, 47.9, 4.8, 48.2, 9.3, 13.2, 4.2, 4.9, 3.9, 3.6, 4.8, 4.2, 9.1, 26. , 32.5, 30.8, 3.9, 10.7, 6.9, 5.5, 4.3, 6.8, 5.6, 82.6, 83.1, 31.8, 6.8, 17.3, 4. , 9.9, 7.1, 3.4, 3.8, 5.2, 3.7, 3.9, 5.3, 4.6, 74.1, 15.9, 3. , 40.2, 27. , 5.8, 99.4, 5.5, 10.8, 7.4, 20.3, 5.3, 6.1, 12.7, 3.8, 3.7, 4. , 6.3, 20.1, 25.4, 7.2, 18.9, 16.1, 5.8, 15.5, 13.7, 5.6, 32.3, 3.4, 8. , 6.4, 4.3, 25.7, 10.5, 4.4, 3.7, 19.6, 17.1, 5.8, 4.4, 6.9, 47.6, 18. , 5.8, 23.9, 20.8, 31.5, ... 7.6, 4.4, 6.9, 5. , 26.2, 43.4, 53. , 8.6, 2.8, 54.3, 7.1, 5.2, 5.7, 21.2, 3.9, 6.1, 4.7, 40.1, 15.8, 5.2, 2.9, 6.8, 4.7, 3.4, 3.7, 4.6, 37. , 25.9, 3. , 19.7, 4.2, 11. , 4.2, 4.6, 5.3, 4. , 2.6, 2.8, 9.6, 7.3, 10.9, 3.4, 8.2, 7.5, 4.6, 3.7, 4.1, 5.8, 4.5, 140.1, 3.5, 3.3, 2.9, 3.5, 5.1, 30.5, 11.1, 7.4, 3.8, 13.8, 5.8, 4.2, 3.5, 3.9, 16.5, 11.1, 6.4, 7.3, 27.4, 7. , 6. , 2.6, 4.9, 5.7, 13.1, 11.9, 3.8, 9.5, 3.3, 25.7, 5.3, 25.1, 17.2, 10.1, 10. , 5. , 12.6, 18.4, 4.1, 3.7, 41.2, 6.2, 8.6, 11.9, 3.8, 3.4, 9. , 5.5, 4.6, 15.6, 4.9, 7.8, 4.3, 7.3, 8.3, 3.5, 12.5, 9.2, 9.4, 9.1, 8.5, 14.3, 7.7, 13.4, 29.2, 4.8, 11.3, 8.4, 3.7, 7.9, 3.9, 3.5, 36.6, 4.7, 34.3, 3.4, 9.2, 13.9, 3.8, 14.5, 7.9, 5.1, 31.3, 8.6, 6.6, 3. , 13.7, 3.1, 20.5, 7.2, 2.8, 4. , 6. , 54.9, 12.3, 7.8, 4.3, 4. , 19.8, 2.7, 21.9, 6.5, 12.2, 183.2, 4.8, 38.2, 11.6, 12.8, 6.3, 10.2, 18.2, 129.5, 16.3, 9.4, 10. , 24. , 5.3, 10.1, 18.2, 6.6, 23.3, 6.6, 9.7], dtype=float32) - vy_error_modeled(mid_date)float3224.2 24.2 21.5 ... 89.5 46.5 46.5
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vy_error_modeled
- units :
- meter/year
array([ 24.2, 24.2, 21.5, 34.2, 83.1, 23.3, 38.8, 24.2, 290.9, 19.4, 58.2, 29.1, 27.7, 145.4, 27.7, 38.8, 290.9, 21.5, 36.4, 290.9, 58.2, 193.9, 48.5, 26.4, 27.7, 145.4, 145.4, 20.8, 48.5, 193.9, 21.5, 145.4, 30.6, 83.1, 25.3, 290.9, 34.2, 26.4, 27.7, 83.1, 290.9, 29.1, 18.2, 32.3, 29.1, 25.3, 22.4, 27.7, 72.7, 290.9, 24.2, 145.4, 193.9, 581.7, 27.7, 29.1, 24.2, 27.7, 290.9, 290.9, 18.8, 20.8, 25.3, 32.3, 21.5, 23.3, 22.4, 17.1, 17.1, 36.4, 290.9, 26.4, 36.4, 29.1, 145.4, 32.3, 20.1, 20.1, 38.8, 23.3, 20.8, 24.2, 193.9, 18.8, 18.2, 193.9, 145.4, 41.6, 72.7, 30.6, 23.3, 145.4, 38.8, 145.4, 23.3, 83.1, 290.9, 19.4, 193.9, 44.7, 38.8, 26.4, 23.3, 17.1, 24.2, 29.1, 19.4, 38.8, 116.3, 193.9, 116.3, 25.3, 41.6, 17.1, 23.3, 21.5, 32.3, 34.2, 581.7, 581.7, 145.4, 36.4, 83.1, 17.1, 30.6, 38.8, 20.8, 19.4, 20.1, 20.8, 26.4, 29.1, 27.7, 581.7, 64.6, 20.1, 193.9, 145.4, 29.1, 581.7, 24.2, 44.7, 32.3, 97. , 20.8, 30.6, 44.7, 22.4, 23.3, 20.8, 32.3, 58.2, 145.4, 30.6, 52.9, 83.1, 30.6, 72.7, 52.9, 27.7, ... 89.5, 22.8, 22. , 25.9, 24.8, 22.8, 21.2, 21.2, 232.7, 129.3, 17.4, 68.4, 28.4, 50.6, 22.8, 22. , 29.8, 25.9, 25.9, 20.4, 37.5, 37.5, 46.5, 20.4, 46.5, 35.3, 20.4, 19.1, 22.8, 33.2, 21.2, 1163.6, 22.8, 23.7, 20.4, 18.5, 31.4, 129.3, 43.1, 40.1, 24.8, 68.4, 28.4, 21.2, 24.8, 22. , 50.6, 50.6, 33.2, 46.5, 166.2, 40.1, 35.3, 19.7, 21.2, 31.4, 46.5, 43.1, 19.7, 37.5, 27.1, 77.6, 19.7, 129.3, 68.4, 40.1, 31.4, 25.9, 40.1, 77.6, 19.7, 19.7, 232.7, 37.5, 55.4, 77.6, 28.4, 18.5, 43.1, 29.8, 23.7, 61.2, 29.8, 28.4, 23.7, 43.1, 50.6, 25.9, 61.2, 29.8, 33.2, 35.3, 46.5, 89.5, 50.6, 61.2, 129.3, 19.7, 35.3, 43.1, 21.2, 31.4, 22. , 25.9, 166.2, 28.4, 166.2, 18.5, 61.2, 89.5, 27.1, 55.4, 55.4, 27.1, 166.2, 31.4, 25.9, 17.9, 77.6, 23.7, 105.8, 37.5, 17.4, 25.9, 31.4, 387.8, 50.6, 33.2, 19.1, 22.8, 68.4, 17.4, 105.8, 35.3, 68.4, 1163.7, 28.4, 166.2, 55.4, 89.5, 29.8, 50.6, 55.4, 387.8, 50.6, 68.4, 77.6, 105.8, 33.2, 55.4, 61.2, 37.5, 89.5, 46.5, 46.5], dtype=float32) - vy_error_slow(mid_date)float324.3 5.0 3.4 6.3 ... 23.3 6.6 9.7
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vy_error_slow
- units :
- meter/year
array([ 4.3, 5. , 3.4, 6.3, 19.5, 7.7, 7.6, 3.2, 109.5, 4. , 20.4, 7.1, 4.1, 30.1, 5.4, 8.2, 59.9, 4.1, 6.5, 43.1, 15. , 42.9, 9.5, 3.3, 5.7, 26. , 21.9, 4.1, 9.8, 37. , 3.7, 26.4, 6.7, 19. , 4.2, 48.6, 7.2, 7.2, 4.4, 15.7, 47. , 4.3, 3.5, 10.2, 11.1, 6. , 5.4, 6.9, 18.6, 39.1, 4.5, 28.5, 33. , 163.4, 6. , 5.5, 5.2, 4.7, 34.3, 44.1, 5. , 3.4, 5.2, 6.3, 3.9, 2.9, 5.4, 5.4, 3.4, 8. , 46. , 6.2, 7.3, 5.7, 24.9, 7.4, 4.9, 4.4, 11.9, 3.7, 5.1, 6.4, 35.8, 4.1, 4.8, 33.5, 28.7, 9.7, 14. , 4.6, 5.1, 22. , 7.7, 30.7, 4.1, 15.1, 48. , 4.8, 48.3, 9.3, 13.2, 4.2, 4.9, 3.9, 3.6, 4.8, 4.2, 9.1, 26. , 32.5, 30.7, 3.9, 10.6, 6.9, 5.5, 4.3, 6.8, 5.6, 82.6, 83.1, 31.8, 6.8, 17.3, 4. , 9.9, 7.2, 3.4, 3.8, 5.2, 3.7, 3.9, 5.3, 4.6, 74.5, 15.9, 3. , 40.2, 27. , 5.8, 99.4, 5.5, 10.8, 7.4, 20.4, 5.3, 6.1, 12.7, 3.8, 3.7, 4. , 6.3, 20.1, 25.4, 7.2, 18.9, 16.1, 5.8, 15.5, 13.7, 5.6, 32.3, 3.4, 8. , 6.4, 4.3, 25.7, 10.5, 4.4, 3.7, 19.7, 17.1, 5.8, 4.4, 6.9, 47.6, 18. , 5.8, 23.9, 20.8, 31.5, ... 7.6, 4.4, 6.9, 5. , 26.2, 43.4, 53. , 8.6, 2.8, 54.3, 7.1, 5.2, 5.7, 21.3, 3.9, 6.1, 4.7, 40.1, 15.8, 5.2, 2.9, 6.8, 4.7, 3.4, 3.7, 4.6, 37. , 25.9, 3. , 19.7, 4.2, 11. , 4.2, 4.6, 5.4, 4. , 2.6, 2.8, 9.6, 7.3, 10.9, 3.4, 8.2, 7.5, 4.6, 3.7, 4.1, 5.8, 4.5, 140. , 3.5, 3.3, 2.9, 3.5, 5.1, 30.6, 11.1, 7.4, 3.8, 13.8, 5.8, 4.2, 3.5, 3.9, 16.5, 11.1, 6.4, 7.3, 27.4, 7. , 6. , 2.6, 4.9, 5.7, 13.2, 11.9, 3.8, 9.5, 3.3, 25.6, 5.3, 25.1, 17.1, 10.1, 10. , 5. , 12.6, 18.4, 4.1, 3.8, 41.2, 6.2, 8.6, 11.9, 3.8, 3.4, 9. , 5.5, 4.6, 15.6, 4.9, 7.7, 4.3, 7.3, 8.3, 3.5, 12.4, 9.2, 9.4, 9.1, 8.4, 14.3, 7.7, 13.4, 29.2, 4.8, 11.2, 8.4, 3.7, 7.9, 3.9, 3.4, 36.6, 4.7, 34.3, 3.4, 9.2, 13.9, 3.8, 14.5, 7.9, 5.1, 31.2, 8.6, 6.6, 3. , 13.8, 3.1, 20.5, 7.2, 2.8, 4. , 6. , 54.9, 12.3, 7.8, 4.3, 4. , 19.8, 2.7, 21.9, 6.5, 12.2, 183.1, 4.8, 38.2, 11.6, 12.8, 6.3, 10.2, 18.1, 128.7, 16.3, 9.5, 10. , 24. , 5.3, 10.1, 18.2, 6.6, 23.3, 6.6, 9.7], dtype=float32) - vy_error_stationary(mid_date)float324.3 5.0 3.4 6.3 ... 23.3 6.6 9.7
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 meter/year identified from an external mask
- standard_name :
- vy_error_stationary
- units :
- meter/year
array([ 4.3, 5. , 3.4, 6.3, 19.5, 7.7, 7.6, 3.2, 109.7, 4. , 20.4, 7. , 4.1, 30.1, 5.4, 8.2, 60. , 4.1, 6.5, 43.1, 15. , 42.9, 9.5, 3.3, 5.7, 26. , 21.9, 4.1, 9.8, 37. , 3.7, 26.4, 6.7, 18.9, 4.2, 48.6, 7.2, 7.2, 4.4, 15.7, 47. , 4.3, 3.5, 10.2, 11.1, 6. , 5.4, 6.9, 18.6, 39.1, 4.5, 28.5, 33. , 163.6, 6. , 5.5, 5.2, 4.7, 34.3, 44. , 5. , 3.4, 5.2, 6.3, 3.9, 2.9, 5.4, 5.4, 3.4, 8. , 46. , 6.2, 7.3, 5.7, 24.9, 7.4, 4.9, 4.4, 11.9, 3.7, 5.1, 6.4, 35.8, 4.1, 4.8, 33.5, 28.7, 9.6, 14. , 4.6, 5.1, 22. , 7.7, 30.7, 4.1, 15.1, 47.9, 4.8, 48.2, 9.3, 13.2, 4.2, 4.9, 3.9, 3.6, 4.8, 4.2, 9.1, 26. , 32.5, 30.8, 3.9, 10.7, 6.9, 5.5, 4.3, 6.8, 5.6, 82.6, 83.1, 31.8, 6.8, 17.3, 4. , 9.9, 7.1, 3.4, 3.8, 5.2, 3.7, 3.9, 5.3, 4.6, 74.1, 15.9, 3. , 40.2, 27. , 5.8, 99.4, 5.5, 10.8, 7.4, 20.3, 5.3, 6.1, 12.7, 3.8, 3.7, 4. , 6.3, 20.1, 25.4, 7.2, 18.9, 16.1, 5.8, 15.5, 13.7, 5.6, 32.3, 3.4, 8. , 6.4, 4.3, 25.7, 10.5, 4.4, 3.7, 19.6, 17.1, 5.8, 4.4, 6.9, 47.6, 18. , 5.8, 23.9, 20.8, 31.5, ... 7.6, 4.4, 6.9, 5. , 26.2, 43.4, 53. , 8.6, 2.8, 54.3, 7.1, 5.2, 5.7, 21.2, 3.9, 6.1, 4.7, 40.1, 15.8, 5.2, 2.9, 6.8, 4.7, 3.4, 3.7, 4.6, 37. , 25.9, 3. , 19.7, 4.2, 11. , 4.2, 4.6, 5.3, 4. , 2.6, 2.8, 9.6, 7.3, 10.9, 3.4, 8.2, 7.5, 4.6, 3.7, 4.1, 5.8, 4.5, 140.1, 3.5, 3.3, 2.9, 3.5, 5.1, 30.5, 11.1, 7.4, 3.8, 13.8, 5.8, 4.2, 3.5, 3.9, 16.5, 11.1, 6.4, 7.3, 27.4, 7. , 6. , 2.6, 4.9, 5.7, 13.1, 11.9, 3.8, 9.5, 3.3, 25.7, 5.3, 25.1, 17.2, 10.1, 10. , 5. , 12.6, 18.4, 4.1, 3.7, 41.2, 6.2, 8.6, 11.9, 3.8, 3.4, 9. , 5.5, 4.6, 15.6, 4.9, 7.8, 4.3, 7.3, 8.3, 3.5, 12.5, 9.2, 9.4, 9.1, 8.5, 14.3, 7.7, 13.4, 29.2, 4.8, 11.3, 8.4, 3.7, 7.9, 3.9, 3.5, 36.6, 4.7, 34.3, 3.4, 9.2, 13.9, 3.8, 14.5, 7.9, 5.1, 31.3, 8.6, 6.6, 3. , 13.7, 3.1, 20.5, 7.2, 2.8, 4. , 6. , 54.9, 12.3, 7.8, 4.3, 4. , 19.8, 2.7, 21.9, 6.5, 12.2, 183.2, 4.8, 38.2, 11.6, 12.8, 6.3, 10.2, 18.2, 129.5, 16.3, 9.4, 10. , 24. , 5.3, 10.1, 18.2, 6.6, 23.3, 6.6, 9.7], dtype=float32) - vy_stable_shift(mid_date)float32-0.3 3.2 -0.8 -6.0 ... 9.8 10.8 3.4
- description :
- applied vy shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vy_stable_shift
- units :
- meter/year
array([-3.000e-01, 3.200e+00, -8.000e-01, -6.000e+00, 7.900e+00, -2.500e+00, -3.900e+00, 0.000e+00, 2.140e+01, -1.100e+00, 1.700e+00, -2.300e+00, 7.000e-01, 6.000e-01, -4.300e+00, -4.800e+00, 1.070e+01, 1.500e+00, -6.700e+00, -3.320e+01, 5.000e-01, 5.410e+01, 3.400e+00, 1.000e+00, -1.000e+00, 4.800e+00, -8.000e+00, 0.000e+00, -3.600e+00, 4.800e+00, 2.000e-01, -1.790e+01, -2.000e-01, 1.070e+01, -9.000e-01, -4.960e+01, -2.000e+00, 7.700e+00, -6.200e+00, 7.800e+00, 3.500e+00, 1.300e+00, -1.000e+00, 1.300e+00, -1.900e+00, -1.900e+00, 1.200e+00, -1.900e+00, -1.270e+01, -2.150e+01, 1.400e+00, 1.380e+01, 2.220e+01, 8.550e+01, -8.000e-01, -9.000e-01, -1.800e+00, 2.800e+00, 1.600e+01, 7.200e+00, 1.200e+00, -1.500e+00, -2.300e+00, -1.200e+00, -8.000e-01, -9.000e-01, -3.100e+00, -2.300e+00, 9.000e-01, -4.000e+00, 1.020e+01, -2.000e+00, -7.100e+00, 6.000e-01, 5.500e+00, -4.200e+00, -1.800e+00, -2.200e+00, -1.300e+00, 4.000e-01, 2.000e-01, -4.500e+00, 3.740e+01, 3.400e+00, -3.200e+00, 1.000e+00, 2.280e+01, 8.000e-01, 5.400e+00, -3.300e+00, 6.000e-01, 0.000e+00, -4.200e+00, 3.200e+00, 3.400e+00, 5.600e+00, 4.930e+01, -4.000e-01, -8.500e+00, -1.600e+00, ... -1.200e+00, 4.400e+00, -2.000e-01, -2.000e-01, 8.500e+00, -2.100e+00, -1.440e+01, 3.100e+00, 1.500e+00, -1.000e+00, 1.600e+00, 0.000e+00, 8.500e+00, -1.400e+00, 0.000e+00, -2.570e+01, 2.800e+00, -2.000e+00, 6.000e-01, 0.000e+00, -7.000e-01, -2.800e+00, -1.100e+00, 4.400e+00, 4.200e+00, 2.200e+00, 1.000e+00, -1.100e+00, 4.500e+00, 1.900e+00, 2.000e-01, -5.400e+00, 6.000e-01, 0.000e+00, -9.000e-01, 1.400e+00, -1.320e+01, -1.700e+00, 1.500e+00, 1.350e+01, 2.200e+00, 1.600e+00, -1.600e+00, -3.900e+00, -4.600e+00, -2.900e+00, -5.000e-01, 1.710e+01, 7.000e-01, 0.000e+00, 2.600e+00, -2.100e+00, 0.000e+00, -1.300e+00, 9.000e-01, 0.000e+00, 1.000e+00, 1.470e+01, 1.700e+00, 1.000e+00, 2.000e-01, -9.900e+00, 9.000e-01, 2.600e+01, 1.100e+01, -6.000e-01, -4.000e-01, -3.200e+00, -4.000e+01, 6.000e-01, 1.200e+00, 1.000e+00, 3.600e+00, 1.800e+00, -6.000e-01, -1.200e+01, -8.000e-01, 7.100e+00, -4.830e+01, 2.200e+00, -2.620e+01, 1.900e+00, -6.600e+00, -2.200e+00, 1.000e+01, -4.100e+00, 5.350e+01, 3.000e+00, -5.900e+00, -4.500e+00, 2.400e+00, -5.000e-01, -1.600e+00, 1.400e+00, 3.400e+00, 9.800e+00, 1.080e+01, 3.400e+00], dtype=float32) - vy_stable_shift_slow(mid_date)float32-0.3 3.2 -0.8 -6.0 ... 9.8 10.8 3.4
- description :
- vy shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vy_stable_shift_slow
- units :
- meter/year
array([-3.000e-01, 3.200e+00, -8.000e-01, -6.000e+00, 8.100e+00, -2.500e+00, -3.900e+00, 0.000e+00, 2.140e+01, -1.100e+00, 1.700e+00, -2.300e+00, 7.000e-01, 7.000e-01, -4.300e+00, -4.800e+00, 1.070e+01, 1.600e+00, -6.700e+00, -3.330e+01, 6.000e-01, 5.440e+01, 3.400e+00, 1.000e+00, -1.000e+00, 4.800e+00, -8.100e+00, 0.000e+00, -3.600e+00, 4.800e+00, 2.000e-01, -1.790e+01, -2.000e-01, 1.070e+01, -9.000e-01, -4.960e+01, -2.000e+00, 7.700e+00, -6.200e+00, 7.900e+00, 3.500e+00, 1.300e+00, -1.000e+00, 1.300e+00, -1.900e+00, -1.900e+00, 1.200e+00, -1.900e+00, -1.260e+01, -2.160e+01, 1.400e+00, 1.380e+01, 2.220e+01, 8.550e+01, -8.000e-01, -9.000e-01, -1.800e+00, 2.800e+00, 1.590e+01, 7.300e+00, 1.200e+00, -1.500e+00, -2.300e+00, -1.200e+00, -8.000e-01, -9.000e-01, -3.100e+00, -2.300e+00, 9.000e-01, -4.000e+00, 1.020e+01, -2.000e+00, -7.200e+00, 6.000e-01, 5.600e+00, -4.200e+00, -1.800e+00, -2.200e+00, -1.300e+00, 4.000e-01, 2.000e-01, -4.500e+00, 3.740e+01, 3.400e+00, -3.200e+00, 1.000e+00, 2.280e+01, 7.000e-01, 5.400e+00, -3.300e+00, 6.000e-01, 0.000e+00, -4.200e+00, 3.400e+00, 3.400e+00, 5.600e+00, 4.930e+01, -4.000e-01, -8.400e+00, -1.700e+00, ... -1.200e+00, 4.400e+00, -2.000e-01, -2.000e-01, 8.400e+00, -2.100e+00, -1.440e+01, 3.200e+00, 1.500e+00, -1.000e+00, 1.600e+00, 0.000e+00, 8.600e+00, -1.400e+00, 0.000e+00, -2.570e+01, 2.800e+00, -2.000e+00, 6.000e-01, 0.000e+00, -7.000e-01, -2.800e+00, -1.100e+00, 4.400e+00, 4.200e+00, 2.200e+00, 1.000e+00, -1.100e+00, 4.500e+00, 1.900e+00, 2.000e-01, -5.300e+00, 6.000e-01, 0.000e+00, -9.000e-01, 1.400e+00, -1.320e+01, -1.700e+00, 1.500e+00, 1.340e+01, 2.200e+00, 1.500e+00, -1.600e+00, -3.900e+00, -4.600e+00, -2.900e+00, -5.000e-01, 1.690e+01, 7.000e-01, 0.000e+00, 2.600e+00, -2.100e+00, 0.000e+00, -1.300e+00, 8.000e-01, 0.000e+00, 1.000e+00, 1.470e+01, 1.700e+00, 1.000e+00, 2.000e-01, -9.900e+00, 9.000e-01, 2.600e+01, 1.100e+01, -6.000e-01, -4.000e-01, -3.200e+00, -4.010e+01, 6.000e-01, 1.200e+00, 1.000e+00, 3.600e+00, 1.700e+00, -6.000e-01, -1.210e+01, -8.000e-01, 7.100e+00, -4.860e+01, 2.200e+00, -2.620e+01, 1.900e+00, -6.600e+00, -2.200e+00, 1.000e+01, -4.100e+00, 5.380e+01, 2.900e+00, -5.900e+00, -4.500e+00, 2.300e+00, -5.000e-01, -1.600e+00, 1.400e+00, 3.400e+00, 9.800e+00, 1.080e+01, 3.400e+00], dtype=float32) - vy_stable_shift_stationary(mid_date)float32-0.3 3.2 -0.8 -6.0 ... 9.8 10.8 3.4
- description :
- vy shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vy_stable_shift_stationary
- units :
- meter/year
array([-3.000e-01, 3.200e+00, -8.000e-01, -6.000e+00, 7.900e+00, -2.500e+00, -3.900e+00, 0.000e+00, 2.140e+01, -1.100e+00, 1.700e+00, -2.300e+00, 7.000e-01, 6.000e-01, -4.300e+00, -4.800e+00, 1.070e+01, 1.500e+00, -6.700e+00, -3.320e+01, 5.000e-01, 5.410e+01, 3.400e+00, 1.000e+00, -1.000e+00, 4.800e+00, -8.000e+00, 0.000e+00, -3.600e+00, 4.800e+00, 2.000e-01, -1.790e+01, -2.000e-01, 1.070e+01, -9.000e-01, -4.960e+01, -2.000e+00, 7.700e+00, -6.200e+00, 7.800e+00, 3.500e+00, 1.300e+00, -1.000e+00, 1.300e+00, -1.900e+00, -1.900e+00, 1.200e+00, -1.900e+00, -1.270e+01, -2.150e+01, 1.400e+00, 1.380e+01, 2.220e+01, 8.550e+01, -8.000e-01, -9.000e-01, -1.800e+00, 2.800e+00, 1.600e+01, 7.200e+00, 1.200e+00, -1.500e+00, -2.300e+00, -1.200e+00, -8.000e-01, -9.000e-01, -3.100e+00, -2.300e+00, 9.000e-01, -4.000e+00, 1.020e+01, -2.000e+00, -7.100e+00, 6.000e-01, 5.500e+00, -4.200e+00, -1.800e+00, -2.200e+00, -1.300e+00, 4.000e-01, 2.000e-01, -4.500e+00, 3.740e+01, 3.400e+00, -3.200e+00, 1.000e+00, 2.280e+01, 8.000e-01, 5.400e+00, -3.300e+00, 6.000e-01, 0.000e+00, -4.200e+00, 3.200e+00, 3.400e+00, 5.600e+00, 4.930e+01, -4.000e-01, -8.500e+00, -1.600e+00, ... -1.200e+00, 4.400e+00, -2.000e-01, -2.000e-01, 8.500e+00, -2.100e+00, -1.440e+01, 3.100e+00, 1.500e+00, -1.000e+00, 1.600e+00, 0.000e+00, 8.500e+00, -1.400e+00, 0.000e+00, -2.570e+01, 2.800e+00, -2.000e+00, 6.000e-01, 0.000e+00, -7.000e-01, -2.800e+00, -1.100e+00, 4.400e+00, 4.200e+00, 2.200e+00, 1.000e+00, -1.100e+00, 4.500e+00, 1.900e+00, 2.000e-01, -5.400e+00, 6.000e-01, 0.000e+00, -9.000e-01, 1.400e+00, -1.320e+01, -1.700e+00, 1.500e+00, 1.350e+01, 2.200e+00, 1.600e+00, -1.600e+00, -3.900e+00, -4.600e+00, -2.900e+00, -5.000e-01, 1.710e+01, 7.000e-01, 0.000e+00, 2.600e+00, -2.100e+00, 0.000e+00, -1.300e+00, 9.000e-01, 0.000e+00, 1.000e+00, 1.470e+01, 1.700e+00, 1.000e+00, 2.000e-01, -9.900e+00, 9.000e-01, 2.600e+01, 1.100e+01, -6.000e-01, -4.000e-01, -3.200e+00, -4.000e+01, 6.000e-01, 1.200e+00, 1.000e+00, 3.600e+00, 1.800e+00, -6.000e-01, -1.200e+01, -8.000e-01, 7.100e+00, -4.830e+01, 2.200e+00, -2.620e+01, 1.900e+00, -6.600e+00, -2.200e+00, 1.000e+01, -4.100e+00, 5.350e+01, 3.000e+00, -5.900e+00, -4.500e+00, 2.400e+00, -5.000e-01, -1.600e+00, 1.400e+00, 3.400e+00, 9.800e+00, 1.080e+01, 3.400e+00], dtype=float32)
- mid_datePandasIndex
PandasIndex(DatetimeIndex(['2017-11-11 04:11:45.280933120', '2017-07-22 04:12:25.815367936', '2017-06-12 04:12:45.944154112', '2017-08-15 04:12:41.874377984', '2017-01-19 04:12:49.477555968', '2018-05-14 04:09:51.589837312', '2017-07-14 04:12:51.977281024', '2018-06-07 04:09:35.005039104', '2018-12-16 04:06:09.176075008', '2017-05-19 04:12:49.742268928', ... '2017-05-23 04:11:32.195375360', '2017-05-31 04:11:34.223706112', '2018-04-16 04:10:33.296293888', '2017-03-12 04:11:48.270008064', '2017-01-15 04:11:35.193293056', '2018-10-09 04:09:53.396051968', '2017-10-06 04:11:40.987761920', '2017-07-26 04:11:49.029760256', '2017-04-21 04:11:32.560144896', '2018-06-11 04:10:57.953189888'], dtype='datetime64[ns]', name='mid_date', length=803, freq=None)) - xPandasIndex
PandasIndex(Index([700252.5, 700372.5, 700492.5, 700612.5, 700732.5, 700852.5, 700972.5, 701092.5, 701212.5, 701332.5, 701452.5, 701572.5, 701692.5, 701812.5, 701932.5, 702052.5, 702172.5, 702292.5, 702412.5, 702532.5, 702652.5, 702772.5, 702892.5, 703012.5, 703132.5, 703252.5, 703372.5, 703492.5, 703612.5, 703732.5, 703852.5, 703972.5, 704092.5, 704212.5, 704332.5, 704452.5, 704572.5, 704692.5, 704812.5, 704932.5, 705052.5, 705172.5, 705292.5, 705412.5, 705532.5, 705652.5, 705772.5, 705892.5, 706012.5, 706132.5, 706252.5, 706372.5, 706492.5, 706612.5, 706732.5, 706852.5, 706972.5, 707092.5, 707212.5, 707332.5, 707452.5, 707572.5, 707692.5, 707812.5, 707932.5, 708052.5, 708172.5, 708292.5, 708412.5, 708532.5, 708652.5, 708772.5, 708892.5], dtype='float64', name='x')) - yPandasIndex
PandasIndex(Index([3394627.5, 3394507.5, 3394387.5, 3394267.5, 3394147.5, 3394027.5, 3393907.5, 3393787.5, 3393667.5, 3393547.5, 3393427.5, 3393307.5, 3393187.5, 3393067.5, 3392947.5, 3392827.5, 3392707.5, 3392587.5, 3392467.5, 3392347.5, 3392227.5, 3392107.5, 3391987.5, 3391867.5, 3391747.5, 3391627.5, 3391507.5, 3391387.5, 3391267.5, 3391147.5, 3391027.5, 3390907.5, 3390787.5, 3390667.5, 3390547.5, 3390427.5, 3390307.5, 3390187.5, 3390067.5, 3389947.5, 3389827.5, 3389707.5, 3389587.5, 3389467.5, 3389347.5, 3389227.5, 3389107.5, 3388987.5, 3388867.5, 3388747.5, 3388627.5, 3388507.5, 3388387.5, 3388267.5, 3388147.5, 3388027.5, 3387907.5, 3387787.5, 3387667.5, 3387547.5, 3387427.5, 3387307.5, 3387187.5, 3387067.5], dtype='float64', name='y'))
- Conventions :
- CF-1.8
- GDAL_AREA_OR_POINT :
- Area
- author :
- ITS_LIVE, a NASA MEaSUREs project (its-live.jpl.nasa.gov)
- autoRIFT_parameter_file :
- http://its-live-data.s3.amazonaws.com/autorift_parameters/v001/autorift_landice_0120m.shp
- datacube_software_version :
- 1.0
- date_created :
- 25-Sep-2023 22:00:23
- date_updated :
- 25-Sep-2023 22:00:23
- geo_polygon :
- [[95.06959008486952, 29.814255053135895], [95.32812062059084, 29.809951334550703], [95.58659184122865, 29.80514261876954], [95.84499718862224, 29.7998293459177], [96.10333011481168, 29.79401200205343], [96.11032804508507, 30.019297601073085], [96.11740568350054, 30.244573983323825], [96.12456379063154, 30.469841094022847], [96.1318031397002, 30.695098878594504], [95.87110827645229, 30.70112924501256], [95.61033817656023, 30.7066371044805], [95.34949964126946, 30.711621947056347], [95.08859948278467, 30.716083310981194], [95.08376623410525, 30.49063893600811], [95.07898726183609, 30.26518607254204], [95.0742620484426, 30.039724763743482], [95.06959008486952, 29.814255053135895]]
- institution :
- NASA Jet Propulsion Laboratory (JPL), California Institute of Technology
- latitude :
- 30.26
- longitude :
- 95.6
- proj_polygon :
- [[700000, 3300000], [725000.0, 3300000.0], [750000.0, 3300000.0], [775000.0, 3300000.0], [800000, 3300000], [800000.0, 3325000.0], [800000.0, 3350000.0], [800000.0, 3375000.0], [800000, 3400000], [775000.0, 3400000.0], [750000.0, 3400000.0], [725000.0, 3400000.0], [700000, 3400000], [700000.0, 3375000.0], [700000.0, 3350000.0], [700000.0, 3325000.0], [700000, 3300000]]
- projection :
- 32646
- s3 :
- s3://its-live-data/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.zarr
- skipped_granules :
- s3://its-live-data/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.json
- time_standard_img1 :
- UTC
- time_standard_img2 :
- UTC
- title :
- ITS_LIVE datacube of image pair velocities
- url :
- https://its-live-data.s3.amazonaws.com/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.zarr
l7_subset.v.mean(dim='mid_date').plot();
Let’s look at Sentinel 1 data. Note here we are selecting for 2 values instead of 1 using DataArray.isin
s1_condition = sample_glacier_raster.satellite_img1.isin(['1A','1B'])
s1_subset = sample_glacier_raster.sel(mid_date = s1_condition)
s1_subset
<xarray.Dataset>
Dimensions: (mid_date: 167, y: 64, x: 73)
Coordinates:
* mid_date (mid_date) datetime64[ns] 2018-12-30T11:41:57...
* x (x) float64 7.003e+05 7.004e+05 ... 7.089e+05
* y (y) float64 3.395e+06 3.395e+06 ... 3.387e+06
mapping int64 0
Data variables: (12/59)
M11 (mid_date, y, x) float32 nan nan nan ... nan nan
M11_dr_to_vr_factor (mid_date) float32 nan nan nan ... nan nan nan
M12 (mid_date, y, x) float32 nan nan nan ... nan nan
M12_dr_to_vr_factor (mid_date) float32 nan nan nan ... nan nan nan
acquisition_date_img1 (mid_date) datetime64[ns] 2018-12-24T11:41:58...
acquisition_date_img2 (mid_date) datetime64[ns] 2019-01-05T11:41:57...
... ...
vy_error_modeled (mid_date) float32 53.7 53.7 53.7 ... 53.7 53.7
vy_error_slow (mid_date) float32 55.8 48.2 77.2 ... 63.3 54.9
vy_error_stationary (mid_date) float32 55.8 48.2 77.2 ... 63.3 54.9
vy_stable_shift (mid_date) float32 0.0 -0.5 0.0 ... 0.5 -0.2 0.0
vy_stable_shift_slow (mid_date) float32 0.0 -0.5 0.0 ... 0.5 -0.2 0.0
vy_stable_shift_stationary (mid_date) float32 0.0 -0.5 0.0 ... 0.5 -0.2 0.0
Attributes: (12/19)
Conventions: CF-1.8
GDAL_AREA_OR_POINT: Area
author: ITS_LIVE, a NASA MEaSUREs project (its-live.j...
autoRIFT_parameter_file: http://its-live-data.s3.amazonaws.com/autorif...
datacube_software_version: 1.0
date_created: 25-Sep-2023 22:00:23
... ...
s3: s3://its-live-data/datacubes/v2/N30E090/ITS_L...
skipped_granules: s3://its-live-data/datacubes/v2/N30E090/ITS_L...
time_standard_img1: UTC
time_standard_img2: UTC
title: ITS_LIVE datacube of image pair velocities
url: https://its-live-data.s3.amazonaws.com/datacu...- mid_date: 167
- y: 64
- x: 73
- mid_date(mid_date)datetime64[ns]2018-12-30T11:41:57.924238080 .....
- description :
- midpoint of image 1 and image 2 acquisition date and time with granule's centroid longitude and latitude as microseconds
- standard_name :
- image_pair_center_date_with_time_separation
array(['2018-12-30T11:41:57.924238080', '2019-09-03T23:37:53.252933888', '2018-03-24T23:37:38.564024320', '2019-04-29T11:41:33.018919936', '2018-02-21T11:41:49.977771008', '2018-05-23T23:37:41.102891008', '2018-04-17T23:37:39.383714048', '2018-08-15T23:37:46.088121344', '2017-11-12T23:37:41.303774976', '2019-12-01T11:42:05.495156992', '2018-09-01T11:41:33.925967616', '2019-04-29T11:41:57.842845952', '2019-02-28T11:41:56.439806976', '2017-12-23T11:41:51.611907072', '2018-01-28T11:41:50.341588736', '2019-02-16T11:41:56.436630016', '2019-10-26T11:42:06.078548992', '2018-06-16T23:37:42.670158080', '2019-12-13T11:42:05.010342912', '2019-05-23T11:41:58.880128000', '2017-06-09T23:37:35.864834048', '2017-11-05T11:41:28.278182912', '2018-12-18T11:41:58.300525056', '2019-11-02T23:37:54.475997952', '2018-11-12T11:41:59.588342016', '2018-07-22T23:37:44.752803072', '2018-05-28T11:41:53.057125888', '2018-03-17T11:41:50.025207040', '2019-02-28T11:41:31.615368192', '2018-06-09T11:41:53.814907904', '2019-02-04T11:41:56.750320896', '2018-09-25T11:41:59.442665984', '2019-11-07T11:41:41.297213952', '2018-11-19T23:37:47.704424960', '2019-07-22T11:42:02.434277120', '2019-08-22T23:37:52.733805056', '2019-10-14T11:42:06.034916096', '2018-09-13T11:41:34.400966912', '2018-10-31T11:41:59.755574016', '2018-07-15T11:41:31.106160128', '2018-04-05T23:37:38.927213056', '2017-07-15T23:37:37.866387968', '2018-01-16T11:41:50.733541888', '2018-03-29T11:41:50.228250112', '2019-09-08T11:42:05.127362048', '2019-03-12T11:41:56.430138112', '2019-03-12T11:41:31.606725888', '2019-06-04T11:41:59.417260032', '2018-04-10T11:41:25.807802112', '2018-02-04T23:37:38.580688896', '2019-01-06T23:37:46.074821120', '2017-10-24T11:41:53.235844096', '2018-12-06T11:41:33.853928192', '2017-03-10T11:41:24.531013888', '2018-10-26T23:37:48.246420736', '2019-01-30T23:37:45.161125376', '2018-04-22T11:41:51.184887040', '2019-04-05T11:41:32.092100352', '2017-02-14T11:41:31.054558976', '2018-01-04T11:41:51.124605952', '2019-03-24T11:41:56.627609088', '2018-07-03T11:41:55.209844224', '2019-09-20T11:42:05.674106880', '2018-12-13T23:37:46.950547968', '2018-08-08T11:41:57.324167936', '2018-08-27T23:37:46.829088000', '2017-09-18T11:41:27.763760128', '2019-11-19T11:41:41.106263040', '2019-04-17T11:41:32.499998976', '2018-07-27T11:41:56.653082112', '2017-04-22T23:37:33.223821056', '2018-04-10T11:41:50.633784320', '2018-12-25T23:37:46.508174848', '2017-07-08T11:41:49.124670208', '2017-07-20T11:41:49.862352896', '2018-04-22T11:41:26.360446976', '2017-04-03T11:41:44.025274112', '2017-12-23T11:41:26.786955008', '2018-03-29T11:41:25.402782976', '2019-01-18T23:37:45.668065792', '2019-08-03T11:42:03.268125952', '2019-12-20T23:37:53.139560960', '2019-10-02T11:42:06.019076352', '2017-11-29T11:41:52.454964224', '2019-04-05T11:41:56.916538624', '2019-07-10T11:42:01.691311872', '2017-05-28T23:37:35.128368640', '2019-08-27T11:41:39.823414016', '2017-11-05T11:41:53.099537920', '2018-06-21T11:41:54.604439040', '2019-05-11T11:41:58.314996992', '2019-10-26T11:41:41.252053760', '2018-07-15T11:41:55.931112960', '2018-05-16T11:41:52.419403008', '2018-06-04T23:37:41.862818304', '2019-10-09T23:37:54.464960256', '2017-10-12T11:41:53.112715008', '2017-04-10T23:37:32.733376000', '2019-06-16T11:42:00.115079936', '2017-08-13T11:41:51.189140992', '2017-05-09T11:41:45.825836032', '2017-03-10T11:41:36.942978048', '2017-12-06T23:37:40.678709760', '2017-03-17T23:37:31.882273792', '2019-11-26T23:37:53.974541056', '2019-08-15T11:42:04.075201024', '2017-05-21T11:41:21.530678016', '2017-09-30T11:41:52.889129984', '2018-10-19T11:41:59.849235968', '2017-10-24T11:41:28.410891776', '2019-11-19T11:42:05.932244992', '2018-08-08T11:41:32.499727872', '2018-01-04T11:41:26.299654144', '2018-09-13T11:41:59.223865088', '2018-09-20T23:37:47.716177152', '2019-09-27T23:37:54.287362816', '2019-11-07T11:42:06.122681088', '2019-12-25T11:42:04.512456960', '2019-01-23T11:41:32.389010944', '2019-08-27T11:42:04.648368128', '2017-02-26T11:41:30.420127232', '2018-12-06T11:41:58.676313088', '2017-12-11T11:41:52.045748992', '2019-09-15T23:37:53.812195072', '2019-07-10T11:41:36.866359040', '2019-11-14T23:37:54.364015104', '2017-05-21T11:41:46.357173760', '2019-06-28T11:42:00.911909120', '2017-11-17T11:41:52.819232000', '2018-11-07T23:37:48.055180288', '2017-03-29T23:37:32.204541952', '2018-09-08T23:37:47.394586880', '2017-08-01T11:41:50.571265024', '2017-03-22T11:41:43.650596352', '2018-02-09T11:41:25.250663168', '2018-05-16T11:41:27.595991040', '2017-04-27T11:41:20.378429952', '2018-11-24T11:41:59.220183040', '2017-02-02T11:41:31.721573120', '2017-11-24T23:37:41.066265088', '2017-04-27T11:41:45.202870016', '2019-01-23T11:41:57.213449728', '2018-08-20T11:41:33.252745984', '2018-02-09T11:41:50.076130048', '2018-08-03T23:37:45.417901056', '2019-02-11T23:37:47.134389760', '2019-02-04T11:41:31.924854016', '2018-09-25T11:41:34.617198080', '2019-10-21T23:37:54.430170112', '2017-09-06T11:41:52.216432896', '2019-01-11T11:41:57.521125120', '2018-03-05T11:41:49.970988032', '2018-04-29T23:37:39.888431104', '2018-10-07T11:41:59.696813056', '2019-12-08T23:37:53.553250048', '2017-03-22T11:41:18.826670080', '2018-03-12T23:37:38.315841024', '2017-09-13T23:37:40.827760640', '2017-08-25T11:41:51.742906112', '2018-05-11T23:37:40.469989120', '2019-04-17T11:41:57.324439040', '2018-12-01T23:37:47.359770880', '2017-09-18T11:41:52.585116928', '2018-05-04T11:41:51.785919232', '2018-07-10T23:37:43.923248128', '2017-04-15T11:41:44.592363008', '2018-06-28T23:37:43.224507904'], dtype='datetime64[ns]') - x(x)float647.003e+05 7.004e+05 ... 7.089e+05
- description :
- x coordinate of projection
- standard_name :
- projection_x_coordinate
- axis :
- X
- long_name :
- x coordinate of projection
- units :
- metre
array([700252.5, 700372.5, 700492.5, 700612.5, 700732.5, 700852.5, 700972.5, 701092.5, 701212.5, 701332.5, 701452.5, 701572.5, 701692.5, 701812.5, 701932.5, 702052.5, 702172.5, 702292.5, 702412.5, 702532.5, 702652.5, 702772.5, 702892.5, 703012.5, 703132.5, 703252.5, 703372.5, 703492.5, 703612.5, 703732.5, 703852.5, 703972.5, 704092.5, 704212.5, 704332.5, 704452.5, 704572.5, 704692.5, 704812.5, 704932.5, 705052.5, 705172.5, 705292.5, 705412.5, 705532.5, 705652.5, 705772.5, 705892.5, 706012.5, 706132.5, 706252.5, 706372.5, 706492.5, 706612.5, 706732.5, 706852.5, 706972.5, 707092.5, 707212.5, 707332.5, 707452.5, 707572.5, 707692.5, 707812.5, 707932.5, 708052.5, 708172.5, 708292.5, 708412.5, 708532.5, 708652.5, 708772.5, 708892.5]) - y(y)float643.395e+06 3.395e+06 ... 3.387e+06
- description :
- y coordinate of projection
- standard_name :
- projection_y_coordinate
- axis :
- Y
- long_name :
- y coordinate of projection
- units :
- metre
array([3394627.5, 3394507.5, 3394387.5, 3394267.5, 3394147.5, 3394027.5, 3393907.5, 3393787.5, 3393667.5, 3393547.5, 3393427.5, 3393307.5, 3393187.5, 3393067.5, 3392947.5, 3392827.5, 3392707.5, 3392587.5, 3392467.5, 3392347.5, 3392227.5, 3392107.5, 3391987.5, 3391867.5, 3391747.5, 3391627.5, 3391507.5, 3391387.5, 3391267.5, 3391147.5, 3391027.5, 3390907.5, 3390787.5, 3390667.5, 3390547.5, 3390427.5, 3390307.5, 3390187.5, 3390067.5, 3389947.5, 3389827.5, 3389707.5, 3389587.5, 3389467.5, 3389347.5, 3389227.5, 3389107.5, 3388987.5, 3388867.5, 3388747.5, 3388627.5, 3388507.5, 3388387.5, 3388267.5, 3388147.5, 3388027.5, 3387907.5, 3387787.5, 3387667.5, 3387547.5, 3387427.5, 3387307.5, 3387187.5, 3387067.5]) - mapping()int640
- crs_wkt :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- WGS 84
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- WGS 84 / UTM zone 46N
- grid_mapping_name :
- transverse_mercator
- latitude_of_projection_origin :
- 0.0
- longitude_of_central_meridian :
- 93.0
- false_easting :
- 500000.0
- false_northing :
- 0.0
- scale_factor_at_central_meridian :
- 0.9996
- spatial_ref :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- GeoTransform :
- 700192.5 120.0 0.0 3394687.5 0.0 -120.0
array(0)
- M11(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- conversion matrix element (1st row, 1st column) that can be multiplied with vx to give range pixel displacement dr (see Eq. A18 in https://www.mdpi.com/2072-4292/13/4/749)
- grid_mapping :
- mapping
- standard_name :
- conversion_matrix_element_11
- units :
- pixel/(meter/year)
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - M11_dr_to_vr_factor(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- multiplicative factor that converts slant range pixel displacement dr to slant range velocity vr
- standard_name :
- M11_dr_to_vr_factor
- units :
- meter/(year*pixel)
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - M12(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- conversion matrix element (1st row, 2nd column) that can be multiplied with vy to give range pixel displacement dr (see Eq. A18 in https://www.mdpi.com/2072-4292/13/4/749)
- grid_mapping :
- mapping
- standard_name :
- conversion_matrix_element_12
- units :
- pixel/(meter/year)
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - M12_dr_to_vr_factor(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- multiplicative factor that converts slant range pixel displacement dr to slant range velocity vr
- standard_name :
- M12_dr_to_vr_factor
- units :
- meter/(year*pixel)
array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan], dtype=float32) - acquisition_date_img1(mid_date)datetime64[ns]2018-12-24T11:41:58.030734080 .....
- description :
- acquisition date and time of image 1
- standard_name :
- image1_acquition_date
array(['2018-12-24T11:41:58.030734080', '2019-08-28T23:37:52.754460160', '2018-03-18T23:37:38.228302080', '2019-04-23T11:41:32.673425152', '2018-02-15T11:41:49.810621696', '2018-05-17T23:37:40.614904320', '2018-04-11T23:37:38.954653952', '2018-08-09T23:37:45.571847936', '2017-11-06T23:37:41.213552896', '2019-11-25T11:42:05.563342080', '2018-08-26T11:41:33.424268032', '2019-04-23T11:41:57.497350912', '2019-02-22T11:41:56.212375040', '2017-12-17T11:41:51.739784960', '2018-01-22T11:41:50.341702912', '2019-02-10T11:41:56.280463872', '2019-10-20T11:42:05.830819072', '2018-06-10T23:37:42.134734080', '2019-12-07T11:42:05.044720896', '2019-05-17T11:41:58.441488896', '2017-06-03T23:37:35.380610048', '2017-10-30T11:41:28.296257024', '2018-12-12T11:41:58.207891968', '2019-10-27T23:37:54.250460928', '2018-11-06T11:41:59.518813952', '2018-07-16T23:37:44.241677056', '2018-05-22T11:41:52.572083968', '2018-03-11T11:41:49.797033984', '2019-02-22T11:41:31.388447744', '2018-06-03T11:41:53.181125120', '2019-01-29T11:41:56.839920128', '2018-09-19T11:41:59.198030848', '2019-11-01T11:41:41.117229312', '2018-11-13T23:37:47.730641920', '2019-07-16T11:42:01.891853056', '2019-08-16T23:37:52.331518976', '2019-10-08T11:42:05.856997888', '2018-09-07T11:41:34.066016000', '2018-10-25T11:41:59.630284032', '2018-07-09T11:41:30.473315072', ... '2017-11-11T11:41:52.737861888', '2018-11-01T23:37:48.017517056', '2017-03-23T23:37:31.793750016', '2018-09-02T23:37:47.053758976', '2017-07-26T11:41:50.082296064', '2017-03-16T11:41:43.372389888', '2018-02-03T11:41:25.154222848', '2018-05-10T11:41:27.082804992', '2017-04-21T11:41:19.897232896', '2018-11-18T11:41:59.295656960', '2017-01-27T11:41:31.661045760', '2017-11-18T23:37:41.051783936', '2017-04-21T11:41:44.722187008', '2019-01-17T11:41:57.206746880', '2018-08-14T11:41:32.719596032', '2018-02-03T11:41:49.981231872', '2018-07-28T23:37:44.902497024', '2019-02-05T23:37:44.616735232', '2019-01-29T11:41:32.014967040', '2018-09-19T11:41:34.374105088', '2019-10-15T23:37:54.227848960', '2017-08-31T11:41:51.826288896', '2019-01-05T11:41:57.455292672', '2018-02-27T11:41:49.784488704', '2018-04-23T23:37:39.451952128', '2018-10-01T11:41:59.325461760', '2019-12-02T23:37:53.540507904', '2017-03-16T11:41:18.548463104', '2018-03-06T23:37:38.042767872', '2017-09-07T23:37:40.395532032', '2017-08-19T11:41:51.317884928', '2018-05-05T23:37:39.964064000', '2019-04-11T11:41:56.770703872', '2018-11-25T23:37:47.315982080', '2017-09-12T11:41:52.264914944', '2018-04-28T11:41:51.305278976', '2018-07-04T23:37:43.243410176', '2017-04-09T11:41:44.121721344', '2018-06-22T23:37:42.844361984'], dtype='datetime64[ns]') - acquisition_date_img2(mid_date)datetime64[ns]2019-01-05T11:41:57.455292672 .....
- description :
- acquisition date and time of image 2
- standard_name :
- image2_acquition_date
array(['2019-01-05T11:41:57.455292672', '2019-09-09T23:37:53.369752064', '2018-03-30T23:37:38.539110912', '2019-05-05T11:41:32.983569920', '2018-02-27T11:41:49.784488704', '2018-05-29T23:37:41.229844992', '2018-04-23T23:37:39.451952128', '2018-08-21T23:37:46.242775296', '2017-11-18T23:37:41.051783936', '2019-12-07T11:42:05.044720896', '2018-09-07T11:41:34.066016000', '2019-05-05T11:41:57.807494912', '2019-03-06T11:41:56.286795776', '2017-12-29T11:41:51.141594880', '2018-02-03T11:41:49.981231872', '2019-02-22T11:41:56.212375040', '2019-11-01T11:42:05.944238336', '2018-06-22T23:37:42.844361984', '2019-12-19T11:42:04.593551104', '2019-05-29T11:41:58.937733888', '2017-06-15T23:37:36.007851776', '2017-11-11T11:41:27.918048000', '2018-12-24T11:41:58.030734080', '2019-11-08T23:37:54.319481344', '2018-11-18T11:41:59.295656960', '2018-07-28T23:37:44.902497024', '2018-06-03T11:41:53.181125120', '2018-03-23T11:41:49.892759040', '2019-03-06T11:41:31.461842944', '2018-06-15T11:41:54.087483904', '2019-02-10T11:41:56.280463872', '2018-10-01T11:41:59.325461760', '2019-11-13T11:41:41.094995968', '2018-11-25T23:37:47.315982080', '2019-07-28T11:42:02.595268096', '2019-08-28T23:37:52.754460160', '2019-10-20T11:42:05.830819072', '2018-09-19T11:41:34.374105088', '2018-11-06T11:41:59.518813952', '2018-07-21T11:41:31.377586688', ... '2017-11-23T11:41:52.558380032', '2018-11-13T23:37:47.730641920', '2017-04-04T23:37:32.274688000', '2018-09-14T23:37:47.373610240', '2017-08-07T11:41:50.718781952', '2017-03-28T11:41:43.588171008', '2018-02-15T11:41:24.986696960', '2018-05-22T11:41:27.748157952', '2017-05-03T11:41:20.518784000', '2018-11-30T11:41:58.782473984', '2017-02-08T11:41:31.441846016', '2017-11-30T23:37:40.738510080', '2017-05-03T11:41:45.342711040', '2019-01-29T11:41:56.839920128', '2018-08-26T11:41:33.424268032', '2018-02-15T11:41:49.810621696', '2018-08-09T23:37:45.571847936', '2019-02-17T23:37:49.271634944', '2019-02-10T11:41:31.454482944', '2018-10-01T11:41:34.498452736', '2019-10-27T23:37:54.250460928', '2017-09-12T11:41:52.264914944', '2019-01-17T11:41:57.206746880', '2018-03-11T11:41:49.797033984', '2018-05-05T23:37:39.964064000', '2018-10-13T11:41:59.706161920', '2019-12-14T23:37:53.183587072', '2017-03-28T11:41:18.764244992', '2018-03-18T23:37:38.228302080', '2017-09-19T23:37:40.918177280', '2017-08-31T11:41:51.826288896', '2018-05-17T23:37:40.614904320', '2019-04-23T11:41:57.497350912', '2018-12-07T23:37:47.041310720', '2017-09-24T11:41:52.563493888', '2018-05-10T11:41:51.905702912', '2018-07-16T23:37:44.241677056', '2017-04-21T11:41:44.722187008', '2018-07-04T23:37:43.243410176'], dtype='datetime64[ns]') - autoRIFT_software_version(mid_date)object'1.4.0' '1.4.0' ... '1.4.0' '1.4.0'
- description :
- version of autoRIFT software
- standard_name :
- autoRIFT_software_version
array(['1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0', '1.4.0'], dtype=object) - chip_size_height(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- chip_size_coordinates :
- Optical data: chip_size_coordinates = 'image projection geometry: width = x, height = y'. Radar data: chip_size_coordinates = 'radar geometry: width = range, height = azimuth'
- description :
- height of search template (chip)
- grid_mapping :
- mapping
- standard_name :
- chip_size_height
- units :
- m
- y_pixel_size :
- 10.0
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - chip_size_width(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- chip_size_coordinates :
- Optical data: chip_size_coordinates = 'image projection geometry: width = x, height = y'. Radar data: chip_size_coordinates = 'radar geometry: width = range, height = azimuth'
- description :
- width of search template (chip)
- grid_mapping :
- mapping
- standard_name :
- chip_size_width
- units :
- m
- x_pixel_size :
- 10.0
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - date_center(mid_date)datetime64[ns]2018-12-30T11:41:57.743013888 .....
- description :
- midpoint of image 1 and image 2 acquisition date
- standard_name :
- image_pair_center_date
array(['2018-12-30T11:41:57.743013888', '2019-09-03T23:37:53.062106112', '2018-03-24T23:37:38.383706112', '2019-04-29T11:41:32.828496640', '2018-02-21T11:41:49.797555968', '2018-05-23T23:37:40.922373888', '2018-04-17T23:37:39.203302912', '2018-08-15T23:37:45.907312128', '2017-11-12T23:37:41.132668928', '2019-12-01T11:42:05.304032000', '2018-09-01T11:41:33.745142016', '2019-04-29T11:41:57.652422912', '2019-02-28T11:41:56.249584896', '2017-12-23T11:41:51.440689920', '2018-01-28T11:41:50.161466880', '2019-02-16T11:41:56.246419968', '2019-10-26T11:42:05.887528960', '2018-06-16T23:37:42.489548032', '2019-12-13T11:42:04.819136000', '2019-05-23T11:41:58.689611008', '2017-06-09T23:37:35.694231040', '2017-11-05T11:41:28.107152896', '2018-12-18T11:41:58.119313152', '2019-11-02T23:37:54.284971008', '2018-11-12T11:41:59.407236096', '2018-07-22T23:37:44.572087040', '2018-05-28T11:41:52.876603904', '2018-03-17T11:41:49.844896000', '2019-02-28T11:41:31.425146112', '2018-06-09T11:41:53.634305024', '2019-02-04T11:41:56.560192000', '2018-09-25T11:41:59.261746944', '2019-11-07T11:41:41.106113024', '2018-11-19T23:37:47.523312384', '2019-07-22T11:42:02.243560704', '2019-08-22T23:37:52.542989056', '2019-10-14T11:42:05.843908096', '2018-09-13T11:41:34.220059904', '2018-10-31T11:41:59.574548992', '2018-07-15T11:41:30.925451008', ... '2017-11-17T11:41:52.648121088', '2018-11-07T23:37:47.874078976', '2017-03-29T23:37:32.034219008', '2018-09-08T23:37:47.213684992', '2017-08-01T11:41:50.400538880', '2017-03-22T11:41:43.480280064', '2018-02-09T11:41:25.070459904', '2018-05-16T11:41:27.415481088', '2017-04-27T11:41:20.208009216', '2018-11-24T11:41:59.039065088', '2017-02-02T11:41:31.551446016', '2017-11-24T23:37:40.895147264', '2017-04-27T11:41:45.032449280', '2019-01-23T11:41:57.023333120', '2018-08-20T11:41:33.071932160', '2018-02-09T11:41:49.895927040', '2018-08-03T23:37:45.237173248', '2019-02-11T23:37:46.944185088', '2019-02-04T11:41:31.734725120', '2018-09-25T11:41:34.436279040', '2019-10-21T23:37:54.239154944', '2017-09-06T11:41:52.045602048', '2019-01-11T11:41:57.331020288', '2018-03-05T11:41:49.790761216', '2018-04-29T23:37:39.708007936', '2018-10-07T11:41:59.515812096', '2019-12-08T23:37:53.362048000', '2017-03-22T11:41:18.656354048', '2018-03-12T23:37:38.135535104', '2017-09-13T23:37:40.656854272', '2017-08-25T11:41:51.572087040', '2018-05-11T23:37:40.289484032', '2019-04-17T11:41:57.134028032', '2018-12-01T23:37:47.178646016', '2017-09-18T11:41:52.414204672', '2018-05-04T11:41:51.605490688', '2018-07-10T23:37:43.742543872', '2017-04-15T11:41:44.421954048', '2018-06-28T23:37:43.043886080'], dtype='datetime64[ns]') - date_dt(mid_date)timedelta64[ns]11 days 23:59:59.423217774 ... 1...
- description :
- time separation between acquisition of image 1 and image 2
- standard_name :
- image_pair_time_separation
array([1036799423217774, 1036800576782225, 1036800329589846, 1036800329589846, 1036800000000000, 1036800576782225, 1036800494384765, 1036800659179684, 1036799835205080, 1036799505615234, 1036800659179684, 1036800329589846, 1036800082397459, 1036799423217774, 1036799670410153, 1036799917602540, 1036800082397459, 1036800741577144, 1036799588012693, 1036800494384765, 1036800659179684, 1036799588012693, 1036799835205080, 1036800082397459, 1036799752807621, 1036800659179684, 1036800576782225, 1036800082397459, 1036800082397459, 1036800906372072, 1036799423217774, 1036800164794919, 1036800000000000, 1036799588012693, 1036800741577144, 1036800411987306, 1036800000000000, 1036800329589846, 1036799917602540, 1036800906372072, 1036800411987306, 1036800659179684, 1036799588012693, 1036800329589846, 1036800494384765, 1036799917602540, 1036799917602540, 1036800576782225, 1036800494384765, 1036799835205080, 1036799505615234, 1036800082397459, 1036799423217774, 1036788381958008, 1036799917602540, 1036799258422855, 1036800576782225, 1036800082397459, 1036798846435549, 1036799588012693, ... 1036799917602540, 1036800082397459, 1036799670410153, 1036800823974612, 1036799588012693, 1036800329589846, 1036800329589846, 1036800411987306, 1036800000000000, 1036799423217774, 1036799670410153, 1036800494384765, 1036799835205080, 1036799423217774, 1036799752807621, 1036800494384765, 1036800741577144, 1036799670410153, 1036800411987306, 1036800741577144, 1036799835205080, 1036799752807621, 1036800494384765, 1036800329589846, 1036800659179684, 1036800247192378, 1036799835205080, 1036800659179684, 1036800659179684, 1036799505615234, 1036799752807621, 1036799670410153, 1036800659179684, 1036799670410153, 1036800741577144, 1036799835205080, 1036800659179684, 1036804614257810, 1036799423217774, 1036800164794919, 1036800000000000, 1036800411987306, 1036799752807621, 1036800000000000, 1036800494384765, 1036800411987306, 1036799670410153, 1036800247192378, 1036800164794919, 1036800494384765, 1036800494384765, 1036800659179684, 1036800741577144, 1036799752807621, 1036800329589846, 1036800576782225, 1036800988769531, 1036800576782225, 1036800411987306], dtype='timedelta64[ns]') - floatingice(y, x, mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- floating ice mask, 0 = non-floating-ice, 1 = floating-ice
- flag_meanings :
- non-ice ice
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- floating ice mask
- url :
- https://its-live-data.s3.amazonaws.com/autorift_parameters/v001/N46_0120m_floatingice.tif
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - granule_url(mid_date)object'https://its-live-data.s3.amazon...
- description :
- original granule URL
- standard_name :
- granule_url
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- description :
- light interpolation mask
- flag_meanings :
- measured interpolated
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- interpolated_value_mask
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - landice(y, x, mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- land ice mask, 0 = non-land-ice, 1 = land-ice
- flag_meanings :
- non-ice ice
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- land ice mask
- url :
- https://its-live-data.s3.amazonaws.com/autorift_parameters/v001/N46_0120m_landice.tif
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - mission_img1(mid_date)object'S' 'S' 'S' 'S' ... 'S' 'S' 'S' 'S'
- description :
- id of the mission that acquired image 1
- standard_name :
- image1_mission
array(['S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S'], dtype=object) - mission_img2(mid_date)object'S' 'S' 'S' 'S' ... 'S' 'S' 'S' 'S'
- description :
- id of the mission that acquired image 2
- standard_name :
- image2_mission
array(['S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S', 'S'], dtype=object) - roi_valid_percentage(mid_date)float3298.9 97.4 97.0 ... 97.3 96.3 97.5
- description :
- percentage of pixels with a valid velocity estimate determined for the intersection of the full image pair footprint and the region of interest (roi) that defines where autoRIFT tried to estimate a velocity
- standard_name :
- region_of_interest_valid_pixel_percentage
array([98.9, 97.4, 97. , 95.1, 98.2, 94.7, 96.4, 97.6, 98.6, 98.3, 97.7, 95.6, 97.5, 99.2, 98.7, 97.9, 97.4, 97. , 98.5, 97.1, 96.4, 98.4, 98.9, 97.7, 97.9, 96.9, 96.6, 98.4, 96.6, 96.7, 98.3, 98.3, 98. , 97.6, 98.1, 97.6, 96.5, 97.7, 97.6, 97.5, 95.7, 97. , 98.8, 97.4, 98.2, 97.4, 96.1, 96.6, 96.1, 97.5, 98.3, 97.8, 98.4, 96.7, 97.8, 97.9, 96.4, 95.6, 98.2, 98.9, 96.5, 98. , 97.9, 97.7, 98.1, 97.6, 97.7, 98.4, 94.2, 98.2, 93.3, 97.5, 97.7, 97.9, 98.1, 95.1, 97. , 98.7, 96. , 98.4, 98.2, 97.8, 98. , 98.9, 96.7, 98. , 96.2, 97.7, 98.8, 97.5, 97.2, 97.2, 98.3, 93.7, 96.4, 97.1, 97.6, 96.3, 96.4, 98.1, 95.2, 96.2, 98.2, 96.6, 98. , 98.1, 95.4, 98.2, 96.6, 97.7, 99. , 97.6, 98.2, 98.2, 97.1, 97.1, 98.5, 98.7, 97.7, 98.3, 97.3, 98.8, 99.2, 97.4, 97.1, 97.9, 96.5, 98. , 98.8, 97.4, 96.5, 97.1, 98.1, 97.7, 97.4, 94.7, 94.7, 98.4, 98.5, 97.8, 96.2, 98.7, 97.6, 98.4, 97.3, 97.1, 97.3, 97.8, 96.7, 98.4, 99. , 98.3, 96.3, 96. , 98. , 96.6, 97.3, 97.6, 98.2, 94.8, 94. , 98.2, 98.4, 96. , 97.3, 96.3, 97.5], dtype=float32) - satellite_img1(mid_date)object'1A' '1A' '1A' ... '1A' '1A' '1A'
- description :
- id of the satellite that acquired image 1
- standard_name :
- image1_satellite
array(['1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A'], dtype=object) - satellite_img2(mid_date)object'1A' '1A' '1A' ... '1A' '1A' '1A'
- description :
- id of the satellite that acquired image 2
- standard_name :
- image2_satellite
array(['1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A', '1A'], dtype=object) - sensor_img1(mid_date)object'C' 'C' 'C' 'C' ... 'C' 'C' 'C' 'C'
- description :
- id of the sensor that acquired image 1
- standard_name :
- image1_sensor
array(['C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C'], dtype=object) - sensor_img2(mid_date)object'C' 'C' 'C' 'C' ... 'C' 'C' 'C' 'C'
- description :
- id of the sensor that acquired image 2
- standard_name :
- image2_sensor
array(['C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C'], dtype=object) - stable_count_slow(mid_date)float641.98e+04 1.72e+04 ... 1.194e+04
- description :
- number of valid pixels over slowest 25% of ice
- standard_name :
- stable_count_slow
- units :
- count
array([19799., 17195., 47883., 4658., 7567., 20397., 43648., 20289., 20279., 7105., 58452., 36966., 62930., 26160., 21155., 4129., 58626., 3285., 12619., 5165., 54401., 55985., 19818., 61986., 65055., 8541., 59144., 9999., 18418., 59788., 10678., 25840., 43763., 59980., 20353., 17750., 45604., 58960., 59699., 55922., 29284., 10764., 19706., 59573., 24047., 57531., 3809., 62284., 12150., 58105., 15562., 3899., 52651., 33728., 63845., 6815., 49968., 64976., 52607., 20163., 43658., 19032., 18194., 62684., 19985., 16253., 60591., 53855., 44007., 20996., 49828., 64087., 65398., 20020., 23695., 63665., 51794., 1546., 9671., 15173., 24566., 1432., 19681., 16615., 50296., 19390., 47567., 62136., 18870., 8557., 4245., 29688., 24326., 8906., 51577., 57582., 13305., 37055., 54244., 22267., 30214., 37609., 8921., 41846., 1790., 25773., 9780., 21968., 40095., 45961., 22306., 55283., 51358., 24538., 99., 6508., 11950., 16260., 42502., 27030., 3917., 16355., 24777., 12715., 47832., 1813., 55687., 19235., 18271., 56430., 41091., 64525., 21846., 63997., 32140., 1440., 51959., 9094., 29104., 485., 43038., 20215., 58466., 12565., 11375., 51770., 33107., 55420., 44071., 25235., 23018., 7192., 41825., 34416., 2793., 13681., 53490., 17934., 26853., 19268., 7892., 8254., 24519., 40610., 10045., 49725., 11942.]) - stable_count_stationary(mid_date)float641.872e+04 1.672e+04 ... 1.143e+04
- description :
- number of valid pixels over stationary or slow-flowing surfaces
- standard_name :
- stable_count_stationary
- units :
- count
array([18717., 16721., 47435., 4622., 6600., 19867., 43002., 19821., 19732., 6035., 58367., 36160., 61939., 24938., 20059., 3068., 57551., 2833., 11585., 4227., 53905., 55929., 18670., 61451., 64153., 8048., 58333., 8982., 18391., 58896., 9593., 25038., 43765., 59518., 19418., 17339., 44561., 58860., 58646., 55848., 28805., 10353., 18722., 58569., 23229., 56465., 3892., 61405., 12172., 57681., 14922., 2728., 52553., 33864., 63275., 6257., 48988., 65050., 52709., 19093., 42666., 18187., 17385., 62093., 19105., 15771., 60427., 53803., 44025., 20108., 49430., 62950., 64821., 19179., 22818., 63708., 50730., 1460., 9731., 14600., 23714., 944., 18681., 15462., 49257., 18485., 47109., 62009., 17667., 7589., 3354., 29666., 23475., 7988., 51054., 57001., 12372., 36537., 53306., 21465., 29305., 37492., 8409., 41372., 1272., 24932., 9780., 21042., 39039., 45899., 21242., 55170., 51306., 23666., 65095., 5951., 10862., 15083., 42417., 26129., 3981., 15224., 23630., 12229., 47704., 1265., 54887., 18329., 17060., 55983., 40595., 63967., 20959., 62882., 32117., 1291., 51962., 7948., 28589., 65450., 42119., 19121., 58401., 11640., 10852., 51198., 32996., 55264., 43520., 24372., 21867., 6096., 41193., 33486., 2234., 13808., 52972., 17497., 25995., 18795., 6995., 7660., 23638., 39592., 9640., 48656., 11432.]) - stable_shift_flag(mid_date)float641.0 1.0 1.0 1.0 ... 1.0 1.0 1.0 1.0
- description :
- flag for applying velocity bias correction: 0 = no correction; 1 = correction from overlapping stable surface mask (stationary or slow-flowing surfaces with velocity < 15 m/yr)(top priority); 2 = correction from slowest 25% of overlapping velocities (second priority)
- standard_name :
- stable_shift_flag
array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.]) - v(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity magnitude
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_velocity
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - v_error(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity magnitude error
- grid_mapping :
- mapping
- standard_name :
- velocity_error
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - va(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity in radar azimuth direction
- grid_mapping :
- mapping
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - va_error(mid_date)float3253.4 46.7 75.4 ... 56.8 61.2 53.3
- description :
- error for velocity in radar azimuth direction
- standard_name :
- va_error
- units :
- meter/year
array([53.4, 46.7, 75.4, 76.3, 62.8, 70.2, 68.2, 48. , 48.7, 61.1, 54.8, 71.8, 75.4, 34.3, 42.2, 70. , 66.5, 55.2, 64.7, 47.7, 65.8, 64.5, 54.1, 71.7, 78.1, 50. , 69.7, 62.9, 83. , 53.4, 62. , 33.3, 75.9, 72.4, 42.4, 53. , 56.3, 54.4, 72.9, 58.8, 69.4, 50.1, 47.1, 65.9, 35.7, 75.6, 85.8, 55.7, 73.2, 67.8, 54.5, 53.9, 62.3, 81.7, 72.5, 63.9, 58.6, 72.9, 60.6, 47.4, 74.7, 43.7, 43.6, 73. , 39.1, 49.9, 52.8, 62.9, 74.9, 40.9, 83.2, 58.6, 68.1, 44.7, 42.3, 70.3, 68.2, 48.6, 79.9, 56.6, 43.5, 65.5, 36.8, 63.9, 65.3, 38.4, 66.7, 57.7, 52.8, 48.6, 45.9, 77.2, 40.2, 74.4, 66.8, 68.8, 33.2, 76.8, 62.7, 40.6, 59.2, 77.3, 55.4, 82.2, 68.1, 40.2, 72.2, 39.1, 72.9, 66.8, 53.1, 55.8, 68.2, 37.5, 53.1, 55.1, 65. , 53.7, 70.1, 39.3, 77.5, 55.5, 45.7, 52.1, 57.9, 66.3, 54.1, 48. , 61.3, 72.1, 75.6, 54. , 44.7, 70.3, 79.6, 73.6, 70. , 63.4, 52.3, 66.3, 58.6, 48.9, 49.9, 55.2, 52.7, 76.8, 77.3, 56. , 79.3, 36.9, 48. , 65.9, 67.4, 60.9, 65.9, 80.9, 75. , 47.4, 34.7, 68.2, 71.9, 63.7, 36.5, 67.1, 56.8, 61.2, 53.3], dtype=float32) - va_error_modeled(mid_date)float3264.4 64.4 64.4 ... 64.4 64.4 64.4
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- va_error_modeled
- units :
- meter/year
array([64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4, 64.4], dtype=float32) - va_error_slow(mid_date)float3253.4 46.7 75.4 ... 56.8 61.2 53.3
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- va_error_slow
- units :
- meter/year
array([53.4, 46.7, 75.4, 76.3, 62.7, 70.2, 68.2, 48. , 48.7, 61.1, 54.8, 71.8, 75.4, 34.3, 42.2, 70. , 66.5, 55.2, 64.7, 47.7, 65.8, 64.5, 54.1, 71.6, 78.1, 50. , 69.7, 62.9, 83. , 53.4, 62. , 33.3, 75.9, 72.4, 42.4, 53. , 56.3, 54.4, 72.9, 58.8, 69.4, 50.1, 47.1, 65.9, 35.7, 75.6, 85.8, 55.7, 73.2, 67.8, 54.5, 53.9, 62.3, 81.7, 72.5, 63.9, 58.6, 72.9, 60.6, 47.4, 74.7, 43.7, 43.6, 73. , 39.1, 49.9, 52.8, 62.9, 74.9, 40.9, 83.2, 58.6, 68.1, 44.7, 42.3, 70.3, 68.2, 48.6, 79.9, 56.6, 43.5, 65.5, 36.8, 63.9, 65.3, 38.4, 66.7, 57.7, 52.8, 48.6, 45.9, 77.2, 40.2, 74.4, 66.8, 68.8, 33.2, 76.8, 62.6, 40.6, 59.2, 77.3, 55.4, 82.2, 68.1, 40.2, 72.2, 39.1, 72.9, 66.8, 53. , 55.8, 68.2, 37.5, 53.1, 55.1, 65. , 53.7, 70.1, 39.3, 77.5, 55.5, 45.7, 52.1, 57.9, 66.3, 54.1, 48. , 61.3, 72.1, 75.6, 54. , 44.7, 70.3, 79.6, 73.6, 70. , 63.4, 52.3, 66.3, 58.6, 48.9, 49.9, 55.2, 52.7, 76.8, 77.3, 56. , 79.3, 36.9, 48. , 65.9, 67.4, 60.9, 65.9, 80.8, 75. , 47.4, 34.7, 68.1, 71.9, 63.7, 36.5, 67.1, 56.8, 61.2, 53.3], dtype=float32) - va_error_stationary(mid_date)float3253.4 46.7 75.4 ... 56.8 61.2 53.3
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- va_error_stationary
- units :
- meter/year
array([53.4, 46.7, 75.4, 76.3, 62.8, 70.2, 68.2, 48. , 48.7, 61.1, 54.8, 71.8, 75.4, 34.3, 42.2, 70. , 66.5, 55.2, 64.7, 47.7, 65.8, 64.5, 54.1, 71.7, 78.1, 50. , 69.7, 62.9, 83. , 53.4, 62. , 33.3, 75.9, 72.4, 42.4, 53. , 56.3, 54.4, 72.9, 58.8, 69.4, 50.1, 47.1, 65.9, 35.7, 75.6, 85.8, 55.7, 73.2, 67.8, 54.5, 53.9, 62.3, 81.7, 72.5, 63.9, 58.6, 72.9, 60.6, 47.4, 74.7, 43.7, 43.6, 73. , 39.1, 49.9, 52.8, 62.9, 74.9, 40.9, 83.2, 58.6, 68.1, 44.7, 42.3, 70.3, 68.2, 48.6, 79.9, 56.6, 43.5, 65.5, 36.8, 63.9, 65.3, 38.4, 66.7, 57.7, 52.8, 48.6, 45.9, 77.2, 40.2, 74.4, 66.8, 68.8, 33.2, 76.8, 62.7, 40.6, 59.2, 77.3, 55.4, 82.2, 68.1, 40.2, 72.2, 39.1, 72.9, 66.8, 53.1, 55.8, 68.2, 37.5, 53.1, 55.1, 65. , 53.7, 70.1, 39.3, 77.5, 55.5, 45.7, 52.1, 57.9, 66.3, 54.1, 48. , 61.3, 72.1, 75.6, 54. , 44.7, 70.3, 79.6, 73.6, 70. , 63.4, 52.3, 66.3, 58.6, 48.9, 49.9, 55.2, 52.7, 76.8, 77.3, 56. , 79.3, 36.9, 48. , 65.9, 67.4, 60.9, 65.9, 80.9, 75. , 47.4, 34.7, 68.2, 71.9, 63.7, 36.5, 67.1, 56.8, 61.2, 53.3], dtype=float32) - va_stable_shift(mid_date)float320.0 0.0 0.0 0.0 ... 0.0 -0.1 0.0
- description :
- applied va shift calibrated using pixels over stable or slow surfaces
- standard_name :
- va_stable_shift
- units :
- meter/year
array([ 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 2.4, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , -8.3, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , -0.1, 0. ], dtype=float32) - va_stable_shift_slow(mid_date)float320.0 0.0 0.0 0.0 ... 0.0 -0.1 0.0
- description :
- va shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- va_stable_shift_slow
- units :
- meter/year
array([ 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 2.4, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , -8.3, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , -0.1, 0. ], dtype=float32) - va_stable_shift_stationary(mid_date)float320.0 0.0 0.0 0.0 ... 0.0 -0.1 0.0
- description :
- va shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- va_stable_shift_stationary
- units :
- meter/year
array([ 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 2.4, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , -8.3, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , -0.1, 0. ], dtype=float32) - vr(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity in radar range direction
- grid_mapping :
- mapping
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - vr_error(mid_date)float3214.2 13.3 24.7 ... 15.7 16.3 15.4
- description :
- error for velocity in radar range direction
- standard_name :
- vr_error
- units :
- meter/year
array([14.2, 13.3, 24.7, 24.6, 17.5, 21. , 20.9, 13.6, 13.3, 16.4, 16.5, 17.7, 21.3, 7.2, 11.5, 19.5, 18.5, 15.6, 16.9, 12.1, 18.9, 20.2, 15. , 22.2, 21.5, 14. , 16.5, 17.2, 28.4, 11.9, 17.6, 7.2, 24.3, 22.9, 9.9, 14.9, 14.9, 16.4, 20.1, 18.4, 21.3, 14.5, 11.9, 18.1, 7.8, 21.2, 29.4, 13.4, 22.6, 22.4, 15.6, 13.7, 18. , 26.8, 22.3, 18.8, 14.8, 22.2, 19.4, 12.4, 21.4, 10.1, 10.4, 22.8, 9.3, 14.1, 16. , 17.9, 23.6, 9.2, 26.4, 16.1, 20.4, 10.2, 9.2, 20.4, 18. , 13.2, 26.5, 16.4, 9.6, 20. , 9.4, 16.3, 17.3, 9. , 19.7, 17.3, 12.8, 11.5, 11.8, 24.5, 8.7, 19.2, 19.8, 20.4, 8. , 24.4, 14.9, 9. , 15.3, 26.8, 16.3, 27.1, 21.2, 8.6, 22.4, 8.9, 20.5, 20.5, 12.5, 17.7, 21.1, 7.9, 15.4, 15.7, 17.4, 14.3, 22.5, 8.4, 25.5, 14.9, 10. , 14.9, 18.3, 19.8, 13.4, 11.1, 15.3, 22.4, 23.8, 16.1, 9.9, 19.7, 26.2, 23.2, 21.3, 17.3, 15.1, 20.1, 15.6, 14. , 15.1, 16.3, 14.8, 24.7, 25.3, 17.8, 24.4, 8.3, 12.7, 18.2, 20.7, 16.6, 20.8, 26.7, 24.5, 13.4, 7.5, 21.2, 18.5, 19.1, 8.3, 18.4, 15.7, 16.3, 15.4], dtype=float32) - vr_error_modeled(mid_date)float3219.8 19.8 19.8 ... 19.8 19.8 19.8
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vr_error_modeled
- units :
- meter/year
array([19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8, 19.8], dtype=float32) - vr_error_slow(mid_date)float3214.2 13.3 24.7 ... 15.7 16.3 15.4
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vr_error_slow
- units :
- meter/year
array([14.2, 13.3, 24.7, 24.6, 17.5, 21. , 20.9, 13.6, 13.3, 16.4, 16.5, 17.7, 21.3, 7.2, 11.5, 19.4, 18.5, 15.6, 16.9, 12.1, 18.9, 20.2, 15. , 22.2, 21.5, 14. , 16.5, 17.2, 28.4, 11.9, 17.6, 7.2, 24.3, 22.9, 9.9, 14.9, 14.9, 16.4, 20.1, 18.4, 21.3, 14.5, 11.9, 18.1, 7.8, 21.2, 29.4, 13.4, 22.6, 22.4, 15.6, 13.7, 18. , 26.8, 22.3, 18.8, 14.8, 22.2, 19.4, 12.4, 21.4, 10.1, 10.4, 22.8, 9.3, 14.1, 16. , 17.9, 23.6, 9.2, 26.4, 16.1, 20.4, 10.2, 9.2, 20.4, 18. , 13.2, 26.5, 16.4, 9.6, 20. , 9.4, 16.3, 17.3, 9. , 19.7, 17.3, 12.8, 11.5, 11.8, 24.5, 8.7, 19.2, 19.8, 20.4, 8. , 24.4, 14.9, 9. , 15.3, 26.8, 16.3, 27.1, 21.2, 8.6, 22.4, 8.9, 20.5, 20.5, 12.5, 17.7, 21.1, 7.9, 15.4, 15.7, 17.4, 14.3, 22.5, 8.4, 25.5, 14.9, 10. , 14.9, 18.3, 19.8, 13.4, 11.1, 15.3, 22.4, 23.8, 16.1, 9.9, 19.7, 26.2, 23.2, 21.3, 17.3, 15.1, 20.1, 15.6, 14. , 15.1, 16.3, 14.8, 24.7, 25.3, 17.8, 24.4, 8.3, 12.7, 18.2, 20.7, 16.6, 20.8, 26.7, 24.5, 13.4, 7.5, 21.2, 18.5, 19.1, 8.3, 18.4, 15.7, 16.3, 15.4], dtype=float32) - vr_error_stationary(mid_date)float3214.2 13.3 24.7 ... 15.7 16.3 15.4
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vr_error_stationary
- units :
- meter/year
array([14.2, 13.3, 24.7, 24.6, 17.5, 21. , 20.9, 13.6, 13.3, 16.4, 16.5, 17.7, 21.3, 7.2, 11.5, 19.5, 18.5, 15.6, 16.9, 12.1, 18.9, 20.2, 15. , 22.2, 21.5, 14. , 16.5, 17.2, 28.4, 11.9, 17.6, 7.2, 24.3, 22.9, 9.9, 14.9, 14.9, 16.4, 20.1, 18.4, 21.3, 14.5, 11.9, 18.1, 7.8, 21.2, 29.4, 13.4, 22.6, 22.4, 15.6, 13.7, 18. , 26.8, 22.3, 18.8, 14.8, 22.2, 19.4, 12.4, 21.4, 10.1, 10.4, 22.8, 9.3, 14.1, 16. , 17.9, 23.6, 9.2, 26.4, 16.1, 20.4, 10.2, 9.2, 20.4, 18. , 13.2, 26.5, 16.4, 9.6, 20. , 9.4, 16.3, 17.3, 9. , 19.7, 17.3, 12.8, 11.5, 11.8, 24.5, 8.7, 19.2, 19.8, 20.4, 8. , 24.4, 14.9, 9. , 15.3, 26.8, 16.3, 27.1, 21.2, 8.6, 22.4, 8.9, 20.5, 20.5, 12.5, 17.7, 21.1, 7.9, 15.4, 15.7, 17.4, 14.3, 22.5, 8.4, 25.5, 14.9, 10. , 14.9, 18.3, 19.8, 13.4, 11.1, 15.3, 22.4, 23.8, 16.1, 9.9, 19.7, 26.2, 23.2, 21.3, 17.3, 15.1, 20.1, 15.6, 14. , 15.1, 16.3, 14.8, 24.7, 25.3, 17.8, 24.4, 8.3, 12.7, 18.2, 20.7, 16.6, 20.8, 26.7, 24.5, 13.4, 7.5, 21.2, 18.5, 19.1, 8.3, 18.4, 15.7, 16.3, 15.4], dtype=float32) - vr_stable_shift(mid_date)float320.0 -2.2 0.0 6.4 ... 2.2 -0.4 0.0
- description :
- applied vr shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vr_stable_shift
- units :
- meter/year
array([ 0. , -2.2, 0. , 6.4, 0. , 0. , 0. , -2.2, 0.1, -2.2, 0. , 4.4, 2.2, -2.2, 0. , 1.8, 0. , 0. , 0. , -4.4, 2.2, -2.2, 2.2, -2.2, -2.2, 0. , 0. , -1.1, 4.4, 1.1, 0. , -2.2, 2.2, 2.2, -2.2, 0. , -0.7, 0. , 0. , -2.2, -2.2, 0. , 0. , 1. , 2.2, -0.2, -2.6, -2.2, 4.2, 0. , 0. , -2.2, 1.1, 0. , -2.2, 2.2, 0. , -3.5, -2.2, 0. , -0.1, 0. , -2.2, 0. , 2.2, -1.2, 0. , 0. , 2.2, -2.2, 1.5, 4.4, -0.5, -1.1, 0. , 1. , -2.2, -2.2, 0. , 0. , -2.2, 1.5, -1.1, 2.1, -2.2, 2.2, -2.2, -2.1, -2.2, 2.2, 2.2, 0. , 0. , -2.1, -2.2, 2.9, 0. , 1.7, 0. , 2.2, 2.2, 0. , -1. , -2.2, 0. , 0. , 0. , 0. , 0.6, -2.2, 0. , 2.7, -1.1, -2.2, 2.2, 0. , 0.5, 0. , 0. , 0. , 1.1, 0. , 0. , -2.2, 2.2, -2.2, 0. , 2.2, 1. , 0.2, 0. , 0. , 2.2, 6.1, 2.2, 0. , -2.2, -0.2, -0.9, -0.7, -2.2, 0. , 0. , 2.2, 0. , 0. , 0. , -2.2, 0. , -4.4, -2.2, 0. , 0. , 0. , 2.2, 5.1, 2.2, 0. , 0. , 2.2, 2. , 0.1, 0. , -2.2, 2.2, -0.4, 0. ], dtype=float32) - vr_stable_shift_slow(mid_date)float320.0 -2.2 0.0 6.4 ... 2.2 -0.4 0.0
- description :
- vr shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vr_stable_shift_slow
- units :
- meter/year
array([ 0. , -2.2, 0. , 6.4, 0. , 0. , 0. , -2.2, 0.1, -2.2, 0. , 4.4, 2.2, -2.2, 0. , 1.8, 0. , 0. , 0. , -4.4, 2.2, -2.2, 2.2, -2.2, -2.2, 0. , 0. , -1.1, 4.4, 1.1, 0. , -2.2, 2.2, 2.2, -2.2, 0. , -0.7, 0. , 0. , -2.2, -2.2, 0. , 0. , 1. , 2.2, -0.2, -2.6, -2.2, 4.2, 0. , 0. , -2.2, 1.1, 0. , -2.2, 2.2, 0. , -3.5, -2.2, 0. , -0.1, 0. , -2.2, 0. , 2.2, -1.2, 0. , 0. , 2.2, -2.2, 1.5, 4.4, -0.5, -1.1, 0. , 1. , -2.2, -2.2, 0. , 0. , -2.2, 1.5, -1.1, 2.1, -2.2, 2.2, -2.2, -2.2, -2.2, 2.2, 2.2, 0. , 0. , -2.1, -2.2, 2.9, 0. , 1.7, 0. , 2.2, 2.2, 0. , -1. , -2.2, 0. , 0. , 0. , 0. , 0.6, -2.2, 0. , 2.7, -1.1, -2.2, 2.2, 0. , 0.5, 0. , 0. , 0. , 1.1, 0. , 0. , -2.2, 2.2, -2.2, 0. , 2.2, 1. , 0.2, 0. , 0. , 2.2, 6.1, 2.2, 0. , -2.2, -0.2, -0.9, -0.7, -2.2, 0. , 0. , 2.2, 0. , 0. , 0. , -2.2, 0. , -4.4, -2.2, 0. , 0. , 0. , 2.2, 5.1, 2.2, 0. , 0. , 2.2, 2. , 0.1, 0. , -2.2, 2.2, -0.4, 0. ], dtype=float32) - vr_stable_shift_stationary(mid_date)float320.0 -2.2 0.0 6.4 ... 2.2 -0.4 0.0
- description :
- vr shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vr_stable_shift_stationary
- units :
- meter/year
array([ 0. , -2.2, 0. , 6.4, 0. , 0. , 0. , -2.2, 0.1, -2.2, 0. , 4.4, 2.2, -2.2, 0. , 1.8, 0. , 0. , 0. , -4.4, 2.2, -2.2, 2.2, -2.2, -2.2, 0. , 0. , -1.1, 4.4, 1.1, 0. , -2.2, 2.2, 2.2, -2.2, 0. , -0.7, 0. , 0. , -2.2, -2.2, 0. , 0. , 1. , 2.2, -0.2, -2.6, -2.2, 4.2, 0. , 0. , -2.2, 1.1, 0. , -2.2, 2.2, 0. , -3.5, -2.2, 0. , -0.1, 0. , -2.2, 0. , 2.2, -1.2, 0. , 0. , 2.2, -2.2, 1.5, 4.4, -0.5, -1.1, 0. , 1. , -2.2, -2.2, 0. , 0. , -2.2, 1.5, -1.1, 2.1, -2.2, 2.2, -2.2, -2.1, -2.2, 2.2, 2.2, 0. , 0. , -2.1, -2.2, 2.9, 0. , 1.7, 0. , 2.2, 2.2, 0. , -1. , -2.2, 0. , 0. , 0. , 0. , 0.6, -2.2, 0. , 2.7, -1.1, -2.2, 2.2, 0. , 0.5, 0. , 0. , 0. , 1.1, 0. , 0. , -2.2, 2.2, -2.2, 0. , 2.2, 1. , 0.2, 0. , 0. , 2.2, 6.1, 2.2, 0. , -2.2, -0.2, -0.9, -0.7, -2.2, 0. , 0. , 2.2, 0. , 0. , 0. , -2.2, 0. , -4.4, -2.2, 0. , 0. , 0. , 2.2, 5.1, 2.2, 0. , 0. , 2.2, 2. , 0.1, 0. , -2.2, 2.2, -0.4, 0. ], dtype=float32) - vx(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity component in x direction
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_x_velocity
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - vx_error(mid_date)float3296.3 85.2 130.4 ... 103.0 100.1
- description :
- best estimate of x_velocity error: vx_error is populated according to the approach used for the velocity bias correction as indicated in "stable_shift_flag"
- standard_name :
- vx_error
- units :
- meter/year
array([ 96.3, 85.2, 130.4, 156.1, 106. , 114.9, 114.4, 90.4, 85.9, 100.5, 116.7, 120.1, 121.6, 60.6, 86. , 111.7, 110.9, 97.4, 100.2, 83.4, 108.8, 130.9, 95.8, 123.6, 119.6, 81. , 112.1, 105.5, 156.3, 87.3, 99.4, 62.6, 146.2, 124.3, 80.1, 94. , 96.4, 112.7, 114.8, 124. , 112.7, 85.1, 87. , 117.3, 68.2, 130.1, 167.9, 92. , 135.3, 122.8, 97.3, 92.7, 119.7, 153.8, 118.3, 113.4, 95.9, 138.2, 131.9, 86.8, 130.6, 78. , 86.9, 132.6, 76.9, 92.7, 115.1, 118. , 149.5, 80.2, 140.2, 100.5, 121.5, 76.7, 77.2, 125.8, 110.7, 98.7, 159.4, 109.1, 82.3, 112.6, 78.5, 109.3, 109. , 70.9, 113.9, 125.3, 84.7, 84.2, 81.4, 141.4, 77.5, 129.3, 115.3, 110.1, 60.4, 126. , 104.9, 72. , 99.4, 166. , 97.2, 144.1, 117.7, 72.1, 146.2, 73.7, 120.7, 133.2, 90.1, 118.7, 137.6, 66.5, 92.4, 92.5, 112.3, 90.3, 134.9, 75.1, 154.8, 99.1, 78.3, 86.6, 123.7, 114. , 103.5, 81.4, 95.6, 121.6, 132.1, 98.2, 74.6, 121.9, 149.6, 150. , 126.1, 110.7, 106.1, 113.6, 93.7, 89. , 99.4, 100. , 93.9, 134.1, 146.1, 117.7, 125.7, 72.7, 89.4, 114.2, 110. , 105.1, 118.4, 157.4, 131.7, 86.1, 66.1, 118.5, 118.7, 111.9, 74.1, 113.5, 99.2, 103. , 100.1], dtype=float32) - vx_error_modeled(mid_date)float3228.8 28.8 28.8 ... 28.8 28.8 28.8
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vx_error_modeled
- units :
- meter/year
array([28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8, 28.8], dtype=float32) - vx_error_slow(mid_date)float3296.3 85.2 130.4 ... 102.9 100.1
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vx_error_slow
- units :
- meter/year
array([ 96.3, 85.2, 130.4, 156.1, 105.9, 114.9, 114.4, 90.4, 85.9, 100.5, 116.7, 120. , 121.6, 60.6, 86. , 111.6, 110.8, 97.4, 100.1, 83.3, 108.8, 130.9, 95.7, 123.6, 119.5, 80.9, 112.1, 105.5, 156.3, 87.3, 99.4, 62.5, 146.2, 124.2, 80.1, 94. , 96.4, 112.7, 114.8, 124. , 112.6, 85. , 86.9, 117.2, 68.2, 130.1, 167.9, 92. , 135.3, 122.7, 97.3, 92.7, 119.7, 153.8, 118.3, 113.4, 95.9, 138.2, 131.9, 86.7, 130.5, 78. , 86.9, 132.6, 76.9, 92.7, 115. , 118. , 149.5, 80.2, 140.2, 100.4, 121.5, 76.7, 77.2, 125.8, 110.6, 98.7, 159.4, 109.1, 82.3, 112.6, 78.5, 109.2, 108.9, 70.8, 113.9, 125.3, 84.7, 84.2, 81.4, 141.4, 77.5, 129.3, 115.2, 110.1, 60.4, 125.9, 104.9, 72. , 99.4, 165.9, 97.2, 144.1, 117.7, 72.1, 146.2, 73.7, 120.6, 133.2, 90.1, 118.7, 137.6, 66.5, 92.4, 92.5, 112.3, 90.2, 134.9, 75.1, 154.8, 99.1, 78.3, 86.6, 123.7, 114. , 103.5, 81.4, 95.6, 121.5, 132.1, 98.2, 74.6, 121.9, 149.6, 149.9, 126.1, 110.6, 106.1, 113.6, 93.7, 89. , 99.4, 99.9, 93.9, 134.1, 146.1, 117.7, 125.7, 72.7, 89.4, 114.2, 110. , 105.1, 118.4, 157.4, 131.7, 86.1, 66.1, 118.4, 118.7, 111.9, 74.1, 113.4, 99.2, 102.9, 100.1], dtype=float32) - vx_error_stationary(mid_date)float3296.3 85.2 130.4 ... 103.0 100.1
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 meter/year identified from an external mask
- standard_name :
- vx_error_stationary
- units :
- meter/year
array([ 96.3, 85.2, 130.4, 156.1, 106. , 114.9, 114.4, 90.4, 85.9, 100.5, 116.7, 120.1, 121.6, 60.6, 86. , 111.7, 110.9, 97.4, 100.2, 83.4, 108.8, 130.9, 95.8, 123.6, 119.6, 81. , 112.1, 105.5, 156.3, 87.3, 99.4, 62.6, 146.2, 124.3, 80.1, 94. , 96.4, 112.7, 114.8, 124. , 112.7, 85.1, 87. , 117.3, 68.2, 130.1, 167.9, 92. , 135.3, 122.8, 97.3, 92.7, 119.7, 153.8, 118.3, 113.4, 95.9, 138.2, 131.9, 86.8, 130.6, 78. , 86.9, 132.6, 76.9, 92.7, 115.1, 118. , 149.5, 80.2, 140.2, 100.5, 121.5, 76.7, 77.2, 125.8, 110.7, 98.7, 159.4, 109.1, 82.3, 112.6, 78.5, 109.3, 109. , 70.9, 113.9, 125.3, 84.7, 84.2, 81.4, 141.4, 77.5, 129.3, 115.3, 110.1, 60.4, 126. , 104.9, 72. , 99.4, 166. , 97.2, 144.1, 117.7, 72.1, 146.2, 73.7, 120.7, 133.2, 90.1, 118.7, 137.6, 66.5, 92.4, 92.5, 112.3, 90.3, 134.9, 75.1, 154.8, 99.1, 78.3, 86.6, 123.7, 114. , 103.5, 81.4, 95.6, 121.6, 132.1, 98.2, 74.6, 121.9, 149.6, 150. , 126.1, 110.7, 106.1, 113.6, 93.7, 89. , 99.4, 100. , 93.9, 134.1, 146.1, 117.7, 125.7, 72.7, 89.4, 114.2, 110. , 105.1, 118.4, 157.4, 131.7, 86.1, 66.1, 118.5, 118.7, 111.9, 74.1, 113.5, 99.2, 103. , 100.1], dtype=float32) - vx_stable_shift(mid_date)float320.0 3.3 0.0 9.6 ... -3.3 -0.6 0.0
- description :
- applied vx shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vx_stable_shift
- units :
- meter/year
array([ 0. , 3.3, 0. , 9.6, 0. , 0. , 0. , 3.3, -0.1, -3.4, 0. , 6.8, 3.4, -3.4, 0. , 2.8, 0. , 0. , 0. , -6.8, -3.3, -3.4, 3.4, 3.3, -3.4, 0. , -0.4, -1.7, 6.7, 1.7, 0. , -3.4, 3.4, -3.3, -3.4, 0. , -1.1, 0. , 0. , -3.3, 3.3, 0. , 0. , 1.6, 3.4, -0.3, -3.9, -3.4, 6.3, 0. , 0. , -3.4, 1.7, 0. , 3.3, -3.3, 0. , -5.2, -3.3, 0. , -0.1, 0. , -3.4, 0. , 3.4, 1.8, 0. , 0. , 3.4, -3.4, -2.2, 6.8, 0.8, -1.7, 0. , 1.5, -3.4, -3.4, 0. , 0. , -3.4, -2.2, -1.7, 3.3, -3.4, 3.4, 3.3, -3.2, -3.4, 3.4, 3.4, 0. , 0. , -1.5, 3.3, -4.3, 0. , -2.6, 0. , 3.4, 3.4, 0. , 1.5, 3.3, 0. , 0. , 0. , 0. , 0.9, -3.3, 0. , 4.1, -1.7, -3.4, -3.3, 0. , 0.8, 0. , 0. , 0. , 1.7, 0. , 0. , 3.3, 3.3, 3.3, 0. , 3.4, 1.5, -0.3, 0. , 0. , 3.4, 9.3, 3.4, 0. , -3.4, -0.3, -1.3, 1.1, -3.4, 0. , 0. , 3.4, 0. , 0. , 0. , -3.3, 0. , -6.8, -3.4, 0. , 0. , 0. , -3.3, 7.8, -3.3, 0. , 0. , -3.3, 3.1, -0.1, 0. , -3.4, -3.3, -0.6, 0. ], dtype=float32) - vx_stable_shift_slow(mid_date)float320.0 3.4 0.0 9.7 ... -3.4 -0.5 0.0
- description :
- vx shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vx_stable_shift_slow
- units :
- meter/year
array([ 0. , 3.4, 0. , 9.7, 0. , 0. , 0. , 3.4, -0.1, -3.3, 0. , 6.6, 3.3, -3.3, 0. , 2.7, 0. , 0. , 0. , -6.6, -3.3, -3.4, 3.3, 3.4, -3.3, 0. , -0.4, -1.7, 6.8, 1.7, 0. , -3.3, 3.4, -3.4, -3.3, 0. , -1.1, 0. , 0. , -3.4, 3.4, 0. , 0. , 1.5, 3.3, -0.3, -3.9, -3.3, 6.4, 0. , 0. , -3.3, 1.7, 0. , 3.4, -3.4, 0. , -5.3, -3.3, 0. , -0.1, 0. , -3.3, 0. , 3.3, 1.8, 0. , 0. , 3.4, -3.3, -2.3, 6.6, 0.8, -1.6, 0. , 1.5, -3.3, -3.4, 0. , 0. , -3.3, -2.2, -1.7, 3.2, -3.3, 3.3, 3.4, -3.3, -3.3, 3.3, 3.3, 0. , 0. , -1.5, 3.4, -4.5, 0. , -2.6, 0. , 3.3, 3.3, 0. , 1.5, 3.4, 0. , 0. , 0. , 0. , 0.9, -3.4, 0. , 4.1, -1.7, -3.3, -3.4, 0. , 0.8, 0. , 0. , 0. , 1.7, 0. , 0. , 3.4, 3.4, 3.4, 0. , 3.3, 1.5, -0.3, 0. , 0. , 3.3, 9.1, 3.4, 0. , -3.4, -0.3, -1.3, 1.1, -3.3, 0. , 0. , 3.3, 0. , 0. , 0. , -3.4, 0. , -6.6, -3.3, 0. , 0. , 0. , -3.4, 7.9, -3.4, 0. , 0. , -3.4, 3. , -0.1, 0. , -3.3, -3.4, -0.5, 0. ], dtype=float32) - vx_stable_shift_stationary(mid_date)float320.0 3.3 0.0 9.6 ... -3.3 -0.6 0.0
- description :
- vx shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vx_stable_shift_stationary
- units :
- meter/year
array([ 0. , 3.3, 0. , 9.6, 0. , 0. , 0. , 3.3, -0.1, -3.4, 0. , 6.8, 3.4, -3.4, 0. , 2.8, 0. , 0. , 0. , -6.8, -3.3, -3.4, 3.4, 3.3, -3.4, 0. , -0.4, -1.7, 6.7, 1.7, 0. , -3.4, 3.4, -3.3, -3.4, 0. , -1.1, 0. , 0. , -3.3, 3.3, 0. , 0. , 1.6, 3.4, -0.3, -3.9, -3.4, 6.3, 0. , 0. , -3.4, 1.7, 0. , 3.3, -3.3, 0. , -5.2, -3.3, 0. , -0.1, 0. , -3.4, 0. , 3.4, 1.8, 0. , 0. , 3.4, -3.4, -2.2, 6.8, 0.8, -1.7, 0. , 1.5, -3.4, -3.4, 0. , 0. , -3.4, -2.2, -1.7, 3.3, -3.4, 3.4, 3.3, -3.2, -3.4, 3.4, 3.4, 0. , 0. , -1.5, 3.3, -4.3, 0. , -2.6, 0. , 3.4, 3.4, 0. , 1.5, 3.3, 0. , 0. , 0. , 0. , 0.9, -3.3, 0. , 4.1, -1.7, -3.4, -3.3, 0. , 0.8, 0. , 0. , 0. , 1.7, 0. , 0. , 3.3, 3.3, 3.3, 0. , 3.4, 1.5, -0.3, 0. , 0. , 3.4, 9.3, 3.4, 0. , -3.4, -0.3, -1.3, 1.1, -3.4, 0. , 0. , 3.4, 0. , 0. , 0. , -3.3, 0. , -6.8, -3.4, 0. , 0. , 0. , -3.3, 7.8, -3.3, 0. , 0. , -3.3, 3.1, -0.1, 0. , -3.4, -3.3, -0.6, 0. ], dtype=float32) - vy(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity component in y direction
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_y_velocity
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - vy_error(mid_date)float3255.8 48.2 77.2 ... 58.2 63.3 54.9
- description :
- best estimate of y_velocity error: vy_error is populated according to the approach used for the velocity bias correction as indicated in "stable_shift_flag"
- standard_name :
- vy_error
- units :
- meter/year
array([55.8, 48.2, 77.2, 81.1, 65.2, 71.3, 69.3, 49.6, 49.9, 63.3, 59.1, 74. , 78. , 35.5, 44.7, 72.4, 68.7, 56.5, 66.8, 49.6, 67. , 68.6, 56.3, 73.4, 80.3, 51. , 72.3, 65.1, 87.5, 55. , 64.1, 35.1, 80.6, 74. , 44.6, 54.5, 58.2, 58.3, 75.1, 63.2, 70.6, 51.3, 49. , 68.7, 37.7, 78.8, 90.7, 57.7, 76.6, 69.6, 55.8, 55.6, 66. , 86.1, 74. , 65.3, 60.4, 76.6, 65. , 49.5, 77.8, 45.7, 46.2, 75.2, 41.4, 51.5, 57. , 66.1, 79.5, 43.1, 85. , 60.6, 69.9, 46.4, 44.3, 73.4, 70.2, 51.5, 84.6, 58.4, 45.6, 67. , 39.4, 66.6, 67.3, 40. , 68.2, 62.3, 53.9, 50.7, 47.9, 81.1, 42.3, 77.1, 68.2, 70. , 34.7, 78.3, 64.8, 42.3, 61. , 83.1, 57. , 84.3, 69.8, 41.9, 76.7, 41.1, 75.3, 70.8, 54.8, 60.1, 72.3, 39.2, 54.5, 56.2, 67.7, 55.9, 74.2, 41.4, 82.4, 58.3, 47.2, 53.4, 62.3, 67.9, 56.7, 49.9, 63.1, 73.6, 77.3, 55.7, 46.3, 73.3, 83.9, 78.3, 73.4, 66.3, 55.1, 67.8, 60.2, 51.1, 53.3, 57.8, 54.2, 78.7, 81.4, 60.3, 80.8, 39. , 50.5, 68.7, 68.5, 63.4, 67.7, 85.5, 76.9, 48.7, 36.4, 69.6, 74.1, 65.3, 38.7, 69.5, 58.2, 63.3, 54.9], dtype=float32) - vy_error_modeled(mid_date)float3253.7 53.7 53.7 ... 53.7 53.7 53.7
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vy_error_modeled
- units :
- meter/year
array([53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7], dtype=float32) - vy_error_slow(mid_date)float3255.8 48.2 77.2 ... 58.2 63.3 54.9
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vy_error_slow
- units :
- meter/year
array([55.8, 48.2, 77.2, 81.1, 65.2, 71.3, 69.3, 49.6, 49.9, 63.3, 59.1, 74. , 78. , 35.5, 44.7, 72.4, 68.7, 56.5, 66.8, 49.6, 67. , 68.6, 56.3, 73.4, 80.3, 51. , 72.3, 65.1, 87.5, 55. , 64.1, 35.1, 80.6, 74. , 44.6, 54.5, 58.2, 58.3, 75.1, 63.2, 70.6, 51.3, 49. , 68.7, 37.7, 78.8, 90.7, 57.7, 76.6, 69.6, 55.8, 55.6, 66. , 86.1, 74. , 65.3, 60.4, 76.6, 65. , 49.6, 77.7, 45.7, 46.2, 75.2, 41.4, 51.5, 57. , 66.1, 79.5, 43.1, 85. , 60.6, 69.9, 46.3, 44.3, 73.4, 70.2, 51.5, 84.6, 58.4, 45.6, 67. , 39.4, 66.6, 67.3, 40. , 68.2, 62.3, 53.9, 50.7, 47.9, 81.1, 42.3, 77.1, 68.2, 70. , 34.7, 78.3, 64.8, 42.3, 61. , 83.1, 57. , 84.3, 69.8, 41.9, 76.7, 41.1, 75.3, 70.8, 54.7, 60.1, 72.3, 39.2, 54.5, 56.2, 67.7, 55.9, 74.2, 41.4, 82.3, 58.3, 47.2, 53.4, 62.3, 67.9, 56.7, 49.9, 63.1, 73.6, 77.3, 55.6, 46.3, 73.3, 83.8, 78.3, 73.4, 66.3, 55.1, 67.8, 60.2, 51.1, 53.3, 57.8, 54.2, 78.7, 81.4, 60.3, 80.8, 39. , 50.5, 68.7, 68.5, 63.4, 67.7, 85.5, 76.9, 48.7, 36.4, 69.5, 74.1, 65.3, 38.7, 69.5, 58.2, 63.3, 54.9], dtype=float32) - vy_error_stationary(mid_date)float3255.8 48.2 77.2 ... 58.2 63.3 54.9
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 meter/year identified from an external mask
- standard_name :
- vy_error_stationary
- units :
- meter/year
array([55.8, 48.2, 77.2, 81.1, 65.2, 71.3, 69.3, 49.6, 49.9, 63.3, 59.1, 74. , 78. , 35.5, 44.7, 72.4, 68.7, 56.5, 66.8, 49.6, 67. , 68.6, 56.3, 73.4, 80.3, 51. , 72.3, 65.1, 87.5, 55. , 64.1, 35.1, 80.6, 74. , 44.6, 54.5, 58.2, 58.3, 75.1, 63.2, 70.6, 51.3, 49. , 68.7, 37.7, 78.8, 90.7, 57.7, 76.6, 69.6, 55.8, 55.6, 66. , 86.1, 74. , 65.3, 60.4, 76.6, 65. , 49.5, 77.8, 45.7, 46.2, 75.2, 41.4, 51.5, 57. , 66.1, 79.5, 43.1, 85. , 60.6, 69.9, 46.4, 44.3, 73.4, 70.2, 51.5, 84.6, 58.4, 45.6, 67. , 39.4, 66.6, 67.3, 40. , 68.2, 62.3, 53.9, 50.7, 47.9, 81.1, 42.3, 77.1, 68.2, 70. , 34.7, 78.3, 64.8, 42.3, 61. , 83.1, 57. , 84.3, 69.8, 41.9, 76.7, 41.1, 75.3, 70.8, 54.8, 60.1, 72.3, 39.2, 54.5, 56.2, 67.7, 55.9, 74.2, 41.4, 82.4, 58.3, 47.2, 53.4, 62.3, 67.9, 56.7, 49.9, 63.1, 73.6, 77.3, 55.7, 46.3, 73.3, 83.9, 78.3, 73.4, 66.3, 55.1, 67.8, 60.2, 51.1, 53.3, 57.8, 54.2, 78.7, 81.4, 60.3, 80.8, 39. , 50.5, 68.7, 68.5, 63.4, 67.7, 85.5, 76.9, 48.7, 36.4, 69.6, 74.1, 65.3, 38.7, 69.5, 58.2, 63.3, 54.9], dtype=float32) - vy_stable_shift(mid_date)float320.0 -0.5 0.0 2.0 ... 0.5 -0.2 0.0
- description :
- applied vy shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vy_stable_shift
- units :
- meter/year
array([ 0. , -0.5, 0. , 2. , 0. , 0. , 0. , -0.5, 0. , -0.7, 0. , 1.4, 0.7, -0.7, 0. , 0.6, 0. , 0. , 0. , -1.4, 0.5, -0.7, 0.7, -0.5, -0.7, 0. , 2.4, -0.3, 1.4, 0.3, 0. , -0.7, 0.7, 0.5, -0.7, 0. , -0.2, 0. , 0. , -0.7, -0.5, 0. , 0. , 0.3, 0.7, -0.1, -0.8, -0.7, 1.3, 0. , 0. , -0.7, 0.3, 0. , -0.5, 0.5, 0. , -1.1, -0.7, 0. , 0. , 0. , -0.7, 0. , 0.7, -0.3, 0. , 0. , 0.7, -0.7, 0.4, 1.4, -0.1, -0.3, 0. , 0.3, -0.7, -0.7, 0. , 0. , -0.7, 0.3, -0.3, 0.7, -0.7, 0.7, -0.5, -0.7, -0.7, 0.7, 0.7, 0. , 0. , -8.8, -0.5, 0.7, 0. , 0.4, 0. , 0.7, 0.7, 0. , -0.2, -0.5, 0. , 0. , 0. , 0. , 0.2, -0.7, 0. , 0.8, -0.3, -0.7, 0.5, 0. , 0.2, 0. , 0. , 0. , 0.4, 0. , 0. , -0.5, 0.7, -0.5, 0. , 0.7, 0.3, 0.1, 0. , 0. , 0.7, 1.9, 0.7, 0. , -0.7, -0.1, -0.3, -0.2, -0.7, 0. , 0. , 0.7, 0. , 0. , 0. , -0.7, 0. , -1.4, -0.7, 0. , 0. , 0. , 0.5, 1.6, 0.5, 0. , 0. , 0.5, 0.6, 0. , 0. , -0.7, 0.5, -0.2, 0. ], dtype=float32) - vy_stable_shift_slow(mid_date)float320.0 -0.5 0.0 2.0 ... 0.5 -0.2 0.0
- description :
- vy shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vy_stable_shift_slow
- units :
- meter/year
array([ 0. , -0.5, 0. , 2. , 0. , 0. , 0. , -0.5, 0. , -0.7, 0. , 1.3, 0.7, -0.7, 0. , 0.5, 0. , 0. , 0. , -1.3, 0.5, -0.7, 0.7, -0.5, -0.7, 0. , 2.4, -0.3, 1.4, 0.3, 0. , -0.7, 0.7, 0.5, -0.7, 0. , -0.2, 0. , 0. , -0.7, -0.5, 0. , 0. , 0.3, 0.7, -0.1, -0.8, -0.7, 1.3, 0. , 0. , -0.7, 0.3, 0. , -0.5, 0.5, 0. , -1.1, -0.7, 0. , 0. , 0. , -0.7, 0. , 0.7, -0.3, 0. , 0. , 0.7, -0.7, 0.4, 1.3, -0.1, -0.3, 0. , 0.3, -0.7, -0.7, 0. , 0. , -0.7, 0.4, -0.3, 0.6, -0.7, 0.7, -0.5, -0.7, -0.7, 0.7, 0.7, 0. , 0. , -8.8, -0.5, 0.7, 0. , 0.4, 0. , 0.7, 0.7, 0. , -0.2, -0.5, 0. , 0. , 0. , 0. , 0.2, -0.7, 0. , 0.8, -0.3, -0.7, 0.5, 0. , 0.2, 0. , 0. , 0. , 0.3, 0. , 0. , -0.5, 0.7, -0.5, 0. , 0.7, 0.3, 0.1, 0. , 0. , 0.7, 1.8, 0.7, 0. , -0.7, -0.1, -0.3, -0.2, -0.7, 0. , 0. , 0.7, 0. , 0. , 0. , -0.7, 0. , -1.3, -0.7, 0. , 0. , 0. , 0.5, 1.6, 0.5, 0. , 0. , 0.5, 0.6, 0. , 0. , -0.7, 0.5, -0.2, 0. ], dtype=float32) - vy_stable_shift_stationary(mid_date)float320.0 -0.5 0.0 2.0 ... 0.5 -0.2 0.0
- description :
- vy shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vy_stable_shift_stationary
- units :
- meter/year
array([ 0. , -0.5, 0. , 2. , 0. , 0. , 0. , -0.5, 0. , -0.7, 0. , 1.4, 0.7, -0.7, 0. , 0.6, 0. , 0. , 0. , -1.4, 0.5, -0.7, 0.7, -0.5, -0.7, 0. , 2.4, -0.3, 1.4, 0.3, 0. , -0.7, 0.7, 0.5, -0.7, 0. , -0.2, 0. , 0. , -0.7, -0.5, 0. , 0. , 0.3, 0.7, -0.1, -0.8, -0.7, 1.3, 0. , 0. , -0.7, 0.3, 0. , -0.5, 0.5, 0. , -1.1, -0.7, 0. , 0. , 0. , -0.7, 0. , 0.7, -0.3, 0. , 0. , 0.7, -0.7, 0.4, 1.4, -0.1, -0.3, 0. , 0.3, -0.7, -0.7, 0. , 0. , -0.7, 0.3, -0.3, 0.7, -0.7, 0.7, -0.5, -0.7, -0.7, 0.7, 0.7, 0. , 0. , -8.8, -0.5, 0.7, 0. , 0.4, 0. , 0.7, 0.7, 0. , -0.2, -0.5, 0. , 0. , 0. , 0. , 0.2, -0.7, 0. , 0.8, -0.3, -0.7, 0.5, 0. , 0.2, 0. , 0. , 0. , 0.4, 0. , 0. , -0.5, 0.7, -0.5, 0. , 0.7, 0.3, 0.1, 0. , 0. , 0.7, 1.9, 0.7, 0. , -0.7, -0.1, -0.3, -0.2, -0.7, 0. , 0. , 0.7, 0. , 0. , 0. , -0.7, 0. , -1.4, -0.7, 0. , 0. , 0. , 0.5, 1.6, 0.5, 0. , 0. , 0.5, 0.6, 0. , 0. , -0.7, 0.5, -0.2, 0. ], dtype=float32)
- mid_datePandasIndex
PandasIndex(DatetimeIndex(['2018-12-30 11:41:57.924238080', '2019-09-03 23:37:53.252933888', '2018-03-24 23:37:38.564024320', '2019-04-29 11:41:33.018919936', '2018-02-21 11:41:49.977771008', '2018-05-23 23:37:41.102891008', '2018-04-17 23:37:39.383714048', '2018-08-15 23:37:46.088121344', '2017-11-12 23:37:41.303774976', '2019-12-01 11:42:05.495156992', ... '2017-09-13 23:37:40.827760640', '2017-08-25 11:41:51.742906112', '2018-05-11 23:37:40.469989120', '2019-04-17 11:41:57.324439040', '2018-12-01 23:37:47.359770880', '2017-09-18 11:41:52.585116928', '2018-05-04 11:41:51.785919232', '2018-07-10 23:37:43.923248128', '2017-04-15 11:41:44.592363008', '2018-06-28 23:37:43.224507904'], dtype='datetime64[ns]', name='mid_date', length=167, freq=None)) - xPandasIndex
PandasIndex(Index([700252.5, 700372.5, 700492.5, 700612.5, 700732.5, 700852.5, 700972.5, 701092.5, 701212.5, 701332.5, 701452.5, 701572.5, 701692.5, 701812.5, 701932.5, 702052.5, 702172.5, 702292.5, 702412.5, 702532.5, 702652.5, 702772.5, 702892.5, 703012.5, 703132.5, 703252.5, 703372.5, 703492.5, 703612.5, 703732.5, 703852.5, 703972.5, 704092.5, 704212.5, 704332.5, 704452.5, 704572.5, 704692.5, 704812.5, 704932.5, 705052.5, 705172.5, 705292.5, 705412.5, 705532.5, 705652.5, 705772.5, 705892.5, 706012.5, 706132.5, 706252.5, 706372.5, 706492.5, 706612.5, 706732.5, 706852.5, 706972.5, 707092.5, 707212.5, 707332.5, 707452.5, 707572.5, 707692.5, 707812.5, 707932.5, 708052.5, 708172.5, 708292.5, 708412.5, 708532.5, 708652.5, 708772.5, 708892.5], dtype='float64', name='x')) - yPandasIndex
PandasIndex(Index([3394627.5, 3394507.5, 3394387.5, 3394267.5, 3394147.5, 3394027.5, 3393907.5, 3393787.5, 3393667.5, 3393547.5, 3393427.5, 3393307.5, 3393187.5, 3393067.5, 3392947.5, 3392827.5, 3392707.5, 3392587.5, 3392467.5, 3392347.5, 3392227.5, 3392107.5, 3391987.5, 3391867.5, 3391747.5, 3391627.5, 3391507.5, 3391387.5, 3391267.5, 3391147.5, 3391027.5, 3390907.5, 3390787.5, 3390667.5, 3390547.5, 3390427.5, 3390307.5, 3390187.5, 3390067.5, 3389947.5, 3389827.5, 3389707.5, 3389587.5, 3389467.5, 3389347.5, 3389227.5, 3389107.5, 3388987.5, 3388867.5, 3388747.5, 3388627.5, 3388507.5, 3388387.5, 3388267.5, 3388147.5, 3388027.5, 3387907.5, 3387787.5, 3387667.5, 3387547.5, 3387427.5, 3387307.5, 3387187.5, 3387067.5], dtype='float64', name='y'))
- Conventions :
- CF-1.8
- GDAL_AREA_OR_POINT :
- Area
- author :
- ITS_LIVE, a NASA MEaSUREs project (its-live.jpl.nasa.gov)
- autoRIFT_parameter_file :
- http://its-live-data.s3.amazonaws.com/autorift_parameters/v001/autorift_landice_0120m.shp
- datacube_software_version :
- 1.0
- date_created :
- 25-Sep-2023 22:00:23
- date_updated :
- 25-Sep-2023 22:00:23
- geo_polygon :
- [[95.06959008486952, 29.814255053135895], [95.32812062059084, 29.809951334550703], [95.58659184122865, 29.80514261876954], [95.84499718862224, 29.7998293459177], [96.10333011481168, 29.79401200205343], [96.11032804508507, 30.019297601073085], [96.11740568350054, 30.244573983323825], [96.12456379063154, 30.469841094022847], [96.1318031397002, 30.695098878594504], [95.87110827645229, 30.70112924501256], [95.61033817656023, 30.7066371044805], [95.34949964126946, 30.711621947056347], [95.08859948278467, 30.716083310981194], [95.08376623410525, 30.49063893600811], [95.07898726183609, 30.26518607254204], [95.0742620484426, 30.039724763743482], [95.06959008486952, 29.814255053135895]]
- institution :
- NASA Jet Propulsion Laboratory (JPL), California Institute of Technology
- latitude :
- 30.26
- longitude :
- 95.6
- proj_polygon :
- [[700000, 3300000], [725000.0, 3300000.0], [750000.0, 3300000.0], [775000.0, 3300000.0], [800000, 3300000], [800000.0, 3325000.0], [800000.0, 3350000.0], [800000.0, 3375000.0], [800000, 3400000], [775000.0, 3400000.0], [750000.0, 3400000.0], [725000.0, 3400000.0], [700000, 3400000], [700000.0, 3375000.0], [700000.0, 3350000.0], [700000.0, 3325000.0], [700000, 3300000]]
- projection :
- 32646
- s3 :
- s3://its-live-data/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.zarr
- skipped_granules :
- s3://its-live-data/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.json
- time_standard_img1 :
- UTC
- time_standard_img2 :
- UTC
- title :
- ITS_LIVE datacube of image pair velocities
- url :
- https://its-live-data.s3.amazonaws.com/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.zarr
s1_subset.v.mean(dim='mid_date').plot();
s2_condition = sample_glacier_raster.satellite_img1.isin(['2A','2B'])
s2_subset = sample_glacier_raster.sel(mid_date=s2_condition)
s2_subset
<xarray.Dataset>
Dimensions: (mid_date: 2342, y: 64, x: 73)
Coordinates:
* mid_date (mid_date) datetime64[ns] 2018-04-14T04:18:49...
* x (x) float64 7.003e+05 7.004e+05 ... 7.089e+05
* y (y) float64 3.395e+06 3.395e+06 ... 3.387e+06
mapping int64 0
Data variables: (12/59)
M11 (mid_date, y, x) float32 nan nan nan ... nan nan
M11_dr_to_vr_factor (mid_date) float32 nan nan nan ... nan nan nan
M12 (mid_date, y, x) float32 nan nan nan ... nan nan
M12_dr_to_vr_factor (mid_date) float32 nan nan nan ... nan nan nan
acquisition_date_img1 (mid_date) datetime64[ns] 2017-12-20T04:21:49...
acquisition_date_img2 (mid_date) datetime64[ns] 2018-08-07T04:15:49...
... ...
vy_error_modeled (mid_date) float32 40.5 28.6 27.4 ... 60.0 30.0
vy_error_slow (mid_date) float32 8.0 1.7 1.2 ... 0.9 12.9 3.6
vy_error_stationary (mid_date) float32 8.0 1.7 1.2 ... 0.9 12.9 3.6
vy_stable_shift (mid_date) float32 8.9 -4.9 -0.7 ... 8.4 2.9
vy_stable_shift_slow (mid_date) float32 8.9 -4.9 -0.7 ... 8.4 2.9
vy_stable_shift_stationary (mid_date) float32 8.9 -4.9 -0.7 ... 8.4 2.9
Attributes: (12/19)
Conventions: CF-1.8
GDAL_AREA_OR_POINT: Area
author: ITS_LIVE, a NASA MEaSUREs project (its-live.j...
autoRIFT_parameter_file: http://its-live-data.s3.amazonaws.com/autorif...
datacube_software_version: 1.0
date_created: 25-Sep-2023 22:00:23
... ...
s3: s3://its-live-data/datacubes/v2/N30E090/ITS_L...
skipped_granules: s3://its-live-data/datacubes/v2/N30E090/ITS_L...
time_standard_img1: UTC
time_standard_img2: UTC
title: ITS_LIVE datacube of image pair velocities
url: https://its-live-data.s3.amazonaws.com/datacu...- mid_date: 2342
- y: 64
- x: 73
- mid_date(mid_date)datetime64[ns]2018-04-14T04:18:49.171219968 .....
- description :
- midpoint of image 1 and image 2 acquisition date and time with granule's centroid longitude and latitude as microseconds
- standard_name :
- image_pair_center_date_with_time_separation
array(['2018-04-14T04:18:49.171219968', '2017-02-10T16:15:50.660901120', '2019-03-15T04:15:44.180925952', ..., '2019-03-30T04:15:51.181000960', '2019-08-29T16:18:15.190612992', '2018-04-24T04:18:14.171119872'], dtype='datetime64[ns]') - x(x)float647.003e+05 7.004e+05 ... 7.089e+05
- description :
- x coordinate of projection
- standard_name :
- projection_x_coordinate
- axis :
- X
- long_name :
- x coordinate of projection
- units :
- metre
array([700252.5, 700372.5, 700492.5, 700612.5, 700732.5, 700852.5, 700972.5, 701092.5, 701212.5, 701332.5, 701452.5, 701572.5, 701692.5, 701812.5, 701932.5, 702052.5, 702172.5, 702292.5, 702412.5, 702532.5, 702652.5, 702772.5, 702892.5, 703012.5, 703132.5, 703252.5, 703372.5, 703492.5, 703612.5, 703732.5, 703852.5, 703972.5, 704092.5, 704212.5, 704332.5, 704452.5, 704572.5, 704692.5, 704812.5, 704932.5, 705052.5, 705172.5, 705292.5, 705412.5, 705532.5, 705652.5, 705772.5, 705892.5, 706012.5, 706132.5, 706252.5, 706372.5, 706492.5, 706612.5, 706732.5, 706852.5, 706972.5, 707092.5, 707212.5, 707332.5, 707452.5, 707572.5, 707692.5, 707812.5, 707932.5, 708052.5, 708172.5, 708292.5, 708412.5, 708532.5, 708652.5, 708772.5, 708892.5]) - y(y)float643.395e+06 3.395e+06 ... 3.387e+06
- description :
- y coordinate of projection
- standard_name :
- projection_y_coordinate
- axis :
- Y
- long_name :
- y coordinate of projection
- units :
- metre
array([3394627.5, 3394507.5, 3394387.5, 3394267.5, 3394147.5, 3394027.5, 3393907.5, 3393787.5, 3393667.5, 3393547.5, 3393427.5, 3393307.5, 3393187.5, 3393067.5, 3392947.5, 3392827.5, 3392707.5, 3392587.5, 3392467.5, 3392347.5, 3392227.5, 3392107.5, 3391987.5, 3391867.5, 3391747.5, 3391627.5, 3391507.5, 3391387.5, 3391267.5, 3391147.5, 3391027.5, 3390907.5, 3390787.5, 3390667.5, 3390547.5, 3390427.5, 3390307.5, 3390187.5, 3390067.5, 3389947.5, 3389827.5, 3389707.5, 3389587.5, 3389467.5, 3389347.5, 3389227.5, 3389107.5, 3388987.5, 3388867.5, 3388747.5, 3388627.5, 3388507.5, 3388387.5, 3388267.5, 3388147.5, 3388027.5, 3387907.5, 3387787.5, 3387667.5, 3387547.5, 3387427.5, 3387307.5, 3387187.5, 3387067.5]) - mapping()int640
- crs_wkt :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- WGS 84
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- WGS 84 / UTM zone 46N
- grid_mapping_name :
- transverse_mercator
- latitude_of_projection_origin :
- 0.0
- longitude_of_central_meridian :
- 93.0
- false_easting :
- 500000.0
- false_northing :
- 0.0
- scale_factor_at_central_meridian :
- 0.9996
- spatial_ref :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- GeoTransform :
- 700192.5 120.0 0.0 3394687.5 0.0 -120.0
array(0)
- M11(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- conversion matrix element (1st row, 1st column) that can be multiplied with vx to give range pixel displacement dr (see Eq. A18 in https://www.mdpi.com/2072-4292/13/4/749)
- grid_mapping :
- mapping
- standard_name :
- conversion_matrix_element_11
- units :
- pixel/(meter/year)
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - M11_dr_to_vr_factor(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- multiplicative factor that converts slant range pixel displacement dr to slant range velocity vr
- standard_name :
- M11_dr_to_vr_factor
- units :
- meter/(year*pixel)
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- M12(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- conversion matrix element (1st row, 2nd column) that can be multiplied with vy to give range pixel displacement dr (see Eq. A18 in https://www.mdpi.com/2072-4292/13/4/749)
- grid_mapping :
- mapping
- standard_name :
- conversion_matrix_element_12
- units :
- pixel/(meter/year)
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - M12_dr_to_vr_factor(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- multiplicative factor that converts slant range pixel displacement dr to slant range velocity vr
- standard_name :
- M12_dr_to_vr_factor
- units :
- meter/(year*pixel)
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- acquisition_date_img1(mid_date)datetime64[ns]2017-12-20T04:21:49 ... 2017-11-...
- description :
- acquisition date and time of image 1
- standard_name :
- image1_acquition_date
array(['2017-12-20T04:21:49.000000000', '2016-09-01T04:15:52.000000000', '2018-09-26T04:15:39.000000000', ..., '2018-10-01T04:15:51.000000000', '2019-06-13T04:15:58.999999744', '2017-11-20T04:20:49.000000000'], dtype='datetime64[ns]') - acquisition_date_img2(mid_date)datetime64[ns]2018-08-07T04:15:49 ... 2018-09-...
- description :
- acquisition date and time of image 2
- standard_name :
- image2_acquition_date
array(['2018-08-07T04:15:49.000000000', '2017-07-23T04:15:49.000000000', '2019-09-01T04:15:49.000000000', ..., '2019-09-26T04:15:51.000000000', '2019-11-15T04:20:31.000000000', '2018-09-26T04:15:39.000000000'], dtype='datetime64[ns]') - autoRIFT_software_version(mid_date)object'1.5.0' '1.5.0' ... '1.5.0' '1.5.0'
- description :
- version of autoRIFT software
- standard_name :
- autoRIFT_software_version
array(['1.5.0', '1.5.0', '1.5.0', ..., '1.5.0', '1.5.0', '1.5.0'], dtype=object) - chip_size_height(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- chip_size_coordinates :
- Optical data: chip_size_coordinates = 'image projection geometry: width = x, height = y'. Radar data: chip_size_coordinates = 'radar geometry: width = range, height = azimuth'
- description :
- height of search template (chip)
- grid_mapping :
- mapping
- standard_name :
- chip_size_height
- units :
- m
- y_pixel_size :
- 10.0
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - chip_size_width(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- chip_size_coordinates :
- Optical data: chip_size_coordinates = 'image projection geometry: width = x, height = y'. Radar data: chip_size_coordinates = 'radar geometry: width = range, height = azimuth'
- description :
- width of search template (chip)
- grid_mapping :
- mapping
- standard_name :
- chip_size_width
- units :
- m
- x_pixel_size :
- 10.0
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - date_center(mid_date)datetime64[ns]2018-04-14T04:18:49 ... 2018-04-...
- description :
- midpoint of image 1 and image 2 acquisition date
- standard_name :
- image_pair_center_date
array(['2018-04-14T04:18:49.000000000', '2017-02-10T16:15:50.500000000', '2019-03-15T04:15:44.000000000', ..., '2019-03-30T04:15:51.000000000', '2019-08-29T16:18:15.000000000', '2018-04-24T04:18:14.000000000'], dtype='datetime64[ns]') - date_dt(mid_date)timedelta64[ns]229 days 23:54:00.087890621 ... ...
- description :
- time separation between acquisition of image 1 and image 2
- standard_name :
- image_pair_time_separation
array([19871640087890621, 28079997363281252, 29376010546875000, ..., 31104000000000000, 13392271582031252, 26783688867187495], dtype='timedelta64[ns]') - floatingice(y, x, mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- floating ice mask, 0 = non-floating-ice, 1 = floating-ice
- flag_meanings :
- non-ice ice
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- floating ice mask
- url :
- https://its-live-data.s3.amazonaws.com/autorift_parameters/v001/N46_0120m_floatingice.tif
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - granule_url(mid_date)object'https://its-live-data.s3.amazon...
- description :
- original granule URL
- standard_name :
- granule_url
array(['https://its-live-data.s3.amazonaws.com/velocity_image_pair/sentinel2/v02/N30E090/S2B_MSIL1C_20171220T042149_N0206_R090_T46RGU_20171220T071238_X_S2B_MSIL1C_20180807T041549_N0206_R090_T46RGU_20180807T080037_G0120V02_P017.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/sentinel2/v02/N30E090/S2A_MSIL1C_20160901T041552_N0204_R090_T46RGV_20160901T042146_X_S2B_MSIL1C_20170723T041549_N0205_R090_T46RGV_20170723T042211_G0120V02_P011.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/sentinel2/v02/N30E090/S2B_MSIL1C_20180926T041539_N0206_R090_T46RFV_20180926T085405_X_S2B_MSIL1C_20190901T041549_N0208_R090_T46RFV_20190901T084626_G0120V02_P051.nc', ..., 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/sentinel2/v02/N30E090/S2A_MSIL1C_20181001T041551_N0206_R090_T46RFV_20181001T072036_X_S2A_MSIL1C_20190926T041551_N0208_R090_T46RFV_20190926T071222_G0120V02_P056.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/sentinel2/v02/N30E090/S2B_MSIL1C_20190613T041559_N0207_R090_T46RFV_20190613T071505_X_S2A_MSIL1C_20191115T042031_N0208_R090_T46RFV_20191115T072359_G0120V02_P056.nc', 'https://its-live-data.s3.amazonaws.com/velocity_image_pair/sentinel2/v02/N30E090/S2B_MSIL1C_20171120T042049_N0206_R090_T46RGV_20171121T055049_X_S2B_MSIL1C_20180926T041539_N0206_R090_T46RGV_20180926T085405_G0120V02_P057.nc'], dtype=object) - interp_mask(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- light interpolation mask
- flag_meanings :
- measured interpolated
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- interpolated_value_mask
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - landice(y, x, mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- land ice mask, 0 = non-land-ice, 1 = land-ice
- flag_meanings :
- non-ice ice
- flag_values :
- [0, 1]
- grid_mapping :
- mapping
- standard_name :
- land ice mask
- url :
- https://its-live-data.s3.amazonaws.com/autorift_parameters/v001/N46_0120m_landice.tif
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - mission_img1(mid_date)object'S' 'S' 'S' 'S' ... 'S' 'S' 'S' 'S'
- description :
- id of the mission that acquired image 1
- standard_name :
- image1_mission
array(['S', 'S', 'S', ..., 'S', 'S', 'S'], dtype=object)
- mission_img2(mid_date)object'S' 'S' 'S' 'S' ... 'S' 'S' 'S' 'S'
- description :
- id of the mission that acquired image 2
- standard_name :
- image2_mission
array(['S', 'S', 'S', ..., 'S', 'S', 'S'], dtype=object)
- roi_valid_percentage(mid_date)float3217.8 11.1 51.2 ... 56.0 56.9 57.6
- description :
- percentage of pixels with a valid velocity estimate determined for the intersection of the full image pair footprint and the region of interest (roi) that defines where autoRIFT tried to estimate a velocity
- standard_name :
- region_of_interest_valid_pixel_percentage
array([17.8, 11.1, 51.2, ..., 56. , 56.9, 57.6], dtype=float32)
- satellite_img1(mid_date)object'2B' '2A' '2B' ... '2A' '2B' '2B'
- description :
- id of the satellite that acquired image 1
- standard_name :
- image1_satellite
array(['2B', '2A', '2B', ..., '2A', '2B', '2B'], dtype=object)
- satellite_img2(mid_date)object'2B' '2B' '2B' ... '2A' '2A' '2B'
- description :
- id of the satellite that acquired image 2
- standard_name :
- image2_satellite
array(['2B', '2B', '2B', ..., '2A', '2A', '2B'], dtype=object)
- sensor_img1(mid_date)object'MSI' 'MSI' 'MSI' ... 'MSI' 'MSI'
- description :
- id of the sensor that acquired image 1
- standard_name :
- image1_sensor
array(['MSI', 'MSI', 'MSI', ..., 'MSI', 'MSI', 'MSI'], dtype=object)
- sensor_img2(mid_date)object'MSI' 'MSI' 'MSI' ... 'MSI' 'MSI'
- description :
- id of the sensor that acquired image 2
- standard_name :
- image2_sensor
array(['MSI', 'MSI', 'MSI', ..., 'MSI', 'MSI', 'MSI'], dtype=object)
- stable_count_slow(mid_date)float648.941e+03 3.531e+04 ... 5.165e+04
- description :
- number of valid pixels over slowest 25% of ice
- standard_name :
- stable_count_slow
- units :
- count
array([ 8941., 35311., 35175., ..., 4723., 3917., 51652.])
- stable_count_stationary(mid_date)float648.446e+03 3.529e+04 ... 5.152e+04
- description :
- number of valid pixels over stationary or slow-flowing surfaces
- standard_name :
- stable_count_stationary
- units :
- count
array([ 8446., 35290., 34638., ..., 3589., 2400., 51519.])
- stable_shift_flag(mid_date)float641.0 1.0 1.0 1.0 ... 1.0 1.0 1.0 1.0
- description :
- flag for applying velocity bias correction: 0 = no correction; 1 = correction from overlapping stable surface mask (stationary or slow-flowing surfaces with velocity < 15 m/yr)(top priority); 2 = correction from slowest 25% of overlapping velocities (second priority)
- standard_name :
- stable_shift_flag
array([1., 1., 1., ..., 1., 1., 1.])
- v(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity magnitude
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_velocity
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - v_error(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity magnitude error
- grid_mapping :
- mapping
- standard_name :
- velocity_error
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - va(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity in radar azimuth direction
- grid_mapping :
- mapping
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - va_error(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- error for velocity in radar azimuth direction
- standard_name :
- va_error
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- va_error_modeled(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- va_error_modeled
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- va_error_slow(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- va_error_slow
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- va_error_stationary(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- va_error_stationary
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- va_stable_shift(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- applied va shift calibrated using pixels over stable or slow surfaces
- standard_name :
- va_stable_shift
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- va_stable_shift_slow(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- va shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- va_stable_shift_slow
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- va_stable_shift_stationary(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- va shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- va_stable_shift_stationary
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- vr(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity in radar range direction
- grid_mapping :
- mapping
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - vr_error(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- error for velocity in radar range direction
- standard_name :
- vr_error
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- vr_error_modeled(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vr_error_modeled
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- vr_error_slow(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vr_error_slow
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- vr_error_stationary(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vr_error_stationary
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- vr_stable_shift(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- applied vr shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vr_stable_shift
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- vr_stable_shift_slow(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- vr shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vr_stable_shift_slow
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- vr_stable_shift_stationary(mid_date)float32nan nan nan nan ... nan nan nan nan
- description :
- vr shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vr_stable_shift_stationary
- units :
- meter/year
array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)
- vx(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity component in x direction
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_x_velocity
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - vx_error(mid_date)float323.3 1.3 1.2 4.9 ... 1.0 5.0 2.0
- description :
- best estimate of x_velocity error: vx_error is populated according to the approach used for the velocity bias correction as indicated in "stable_shift_flag"
- standard_name :
- vx_error
- units :
- meter/year
array([3.3, 1.3, 1.2, ..., 1. , 5. , 2. ], dtype=float32)
- vx_error_modeled(mid_date)float3240.5 28.6 27.4 ... 25.9 60.0 30.0
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vx_error_modeled
- units :
- meter/year
array([40.5, 28.6, 27.4, ..., 25.9, 60. , 30. ], dtype=float32)
- vx_error_slow(mid_date)float323.3 1.3 1.2 4.9 ... 1.0 5.0 2.0
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vx_error_slow
- units :
- meter/year
array([3.3, 1.3, 1.2, ..., 1. , 5. , 2. ], dtype=float32)
- vx_error_stationary(mid_date)float323.3 1.3 1.2 4.9 ... 1.0 5.0 2.0
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 meter/year identified from an external mask
- standard_name :
- vx_error_stationary
- units :
- meter/year
array([3.3, 1.3, 1.2, ..., 1. , 5. , 2. ], dtype=float32)
- vx_stable_shift(mid_date)float32-1.0 -2.1 5.9 ... -5.3 -1.5 -0.7
- description :
- applied vx shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vx_stable_shift
- units :
- meter/year
array([-1. , -2.1, 5.9, ..., -5.3, -1.5, -0.7], dtype=float32)
- vx_stable_shift_slow(mid_date)float32-1.0 -2.1 5.9 ... -5.3 -1.5 -0.7
- description :
- vx shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vx_stable_shift_slow
- units :
- meter/year
array([-1. , -2.1, 5.9, ..., -5.3, -1.5, -0.7], dtype=float32)
- vx_stable_shift_stationary(mid_date)float32-1.0 -2.1 5.9 ... -5.3 -1.5 -0.7
- description :
- vx shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vx_stable_shift_stationary
- units :
- meter/year
array([-1. , -2.1, 5.9, ..., -5.3, -1.5, -0.7], dtype=float32)
- vy(mid_date, y, x)float32nan nan nan nan ... nan nan nan nan
- description :
- velocity component in y direction
- grid_mapping :
- mapping
- standard_name :
- land_ice_surface_y_velocity
- units :
- meter/year
array([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., ... ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], [[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32) - vy_error(mid_date)float328.0 1.7 1.2 7.4 ... 0.9 12.9 3.6
- description :
- best estimate of y_velocity error: vy_error is populated according to the approach used for the velocity bias correction as indicated in "stable_shift_flag"
- standard_name :
- vy_error
- units :
- meter/year
array([ 8. , 1.7, 1.2, ..., 0.9, 12.9, 3.6], dtype=float32)
- vy_error_modeled(mid_date)float3240.5 28.6 27.4 ... 25.9 60.0 30.0
- description :
- 1-sigma error calculated using a modeled error-dt relationship
- standard_name :
- vy_error_modeled
- units :
- meter/year
array([40.5, 28.6, 27.4, ..., 25.9, 60. , 30. ], dtype=float32)
- vy_error_slow(mid_date)float328.0 1.7 1.2 7.4 ... 0.9 12.9 3.6
- description :
- RMSE over slowest 25% of retrieved velocities
- standard_name :
- vy_error_slow
- units :
- meter/year
array([ 8. , 1.7, 1.2, ..., 0.9, 12.9, 3.6], dtype=float32)
- vy_error_stationary(mid_date)float328.0 1.7 1.2 7.4 ... 0.9 12.9 3.6
- description :
- RMSE over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 meter/year identified from an external mask
- standard_name :
- vy_error_stationary
- units :
- meter/year
array([ 8. , 1.7, 1.2, ..., 0.9, 12.9, 3.6], dtype=float32)
- vy_stable_shift(mid_date)float328.9 -4.9 -0.7 12.9 ... -0.6 8.4 2.9
- description :
- applied vy shift calibrated using pixels over stable or slow surfaces
- standard_name :
- vy_stable_shift
- units :
- meter/year
array([ 8.9, -4.9, -0.7, ..., -0.6, 8.4, 2.9], dtype=float32)
- vy_stable_shift_slow(mid_date)float328.9 -4.9 -0.7 12.9 ... -0.6 8.4 2.9
- description :
- vy shift calibrated using valid pixels over slowest 25% of retrieved velocities
- standard_name :
- vy_stable_shift_slow
- units :
- meter/year
array([ 8.9, -4.9, -0.7, ..., -0.6, 8.4, 2.9], dtype=float32)
- vy_stable_shift_stationary(mid_date)float328.9 -4.9 -0.7 12.9 ... -0.6 8.4 2.9
- description :
- vy shift calibrated using valid pixels over stable surfaces, stationary or slow-flowing surfaces with velocity < 15 m/yr identified from an external mask
- standard_name :
- vy_stable_shift_stationary
- units :
- meter/year
array([ 8.9, -4.9, -0.7, ..., -0.6, 8.4, 2.9], dtype=float32)
- mid_datePandasIndex
PandasIndex(DatetimeIndex(['2018-04-14 04:18:49.171219968', '2017-02-10 16:15:50.660901120', '2019-03-15 04:15:44.180925952', '2019-07-20 16:15:55.190603008', '2018-01-31 16:15:50.170811904', '2017-12-17 16:15:50.170508800', '2017-10-16 04:18:49.170811904', '2017-11-27 16:20:45.171105024', '2017-10-08 16:17:55.170906112', '2019-10-23 16:18:15.191001088', ... '2017-12-25 04:21:49.171219968', '2019-10-08 16:18:00.190906112', '2017-11-22 16:16:25.170509056', '2018-01-31 16:17:15.170509056', '2019-07-20 16:15:55.190613248', '2017-07-25 16:20:40.170119168', '2019-10-26 04:18:31.191005952', '2019-03-30 04:15:51.181000960', '2019-08-29 16:18:15.190612992', '2018-04-24 04:18:14.171119872'], dtype='datetime64[ns]', name='mid_date', length=2342, freq=None)) - xPandasIndex
PandasIndex(Index([700252.5, 700372.5, 700492.5, 700612.5, 700732.5, 700852.5, 700972.5, 701092.5, 701212.5, 701332.5, 701452.5, 701572.5, 701692.5, 701812.5, 701932.5, 702052.5, 702172.5, 702292.5, 702412.5, 702532.5, 702652.5, 702772.5, 702892.5, 703012.5, 703132.5, 703252.5, 703372.5, 703492.5, 703612.5, 703732.5, 703852.5, 703972.5, 704092.5, 704212.5, 704332.5, 704452.5, 704572.5, 704692.5, 704812.5, 704932.5, 705052.5, 705172.5, 705292.5, 705412.5, 705532.5, 705652.5, 705772.5, 705892.5, 706012.5, 706132.5, 706252.5, 706372.5, 706492.5, 706612.5, 706732.5, 706852.5, 706972.5, 707092.5, 707212.5, 707332.5, 707452.5, 707572.5, 707692.5, 707812.5, 707932.5, 708052.5, 708172.5, 708292.5, 708412.5, 708532.5, 708652.5, 708772.5, 708892.5], dtype='float64', name='x')) - yPandasIndex
PandasIndex(Index([3394627.5, 3394507.5, 3394387.5, 3394267.5, 3394147.5, 3394027.5, 3393907.5, 3393787.5, 3393667.5, 3393547.5, 3393427.5, 3393307.5, 3393187.5, 3393067.5, 3392947.5, 3392827.5, 3392707.5, 3392587.5, 3392467.5, 3392347.5, 3392227.5, 3392107.5, 3391987.5, 3391867.5, 3391747.5, 3391627.5, 3391507.5, 3391387.5, 3391267.5, 3391147.5, 3391027.5, 3390907.5, 3390787.5, 3390667.5, 3390547.5, 3390427.5, 3390307.5, 3390187.5, 3390067.5, 3389947.5, 3389827.5, 3389707.5, 3389587.5, 3389467.5, 3389347.5, 3389227.5, 3389107.5, 3388987.5, 3388867.5, 3388747.5, 3388627.5, 3388507.5, 3388387.5, 3388267.5, 3388147.5, 3388027.5, 3387907.5, 3387787.5, 3387667.5, 3387547.5, 3387427.5, 3387307.5, 3387187.5, 3387067.5], dtype='float64', name='y'))
- Conventions :
- CF-1.8
- GDAL_AREA_OR_POINT :
- Area
- author :
- ITS_LIVE, a NASA MEaSUREs project (its-live.jpl.nasa.gov)
- autoRIFT_parameter_file :
- http://its-live-data.s3.amazonaws.com/autorift_parameters/v001/autorift_landice_0120m.shp
- datacube_software_version :
- 1.0
- date_created :
- 25-Sep-2023 22:00:23
- date_updated :
- 25-Sep-2023 22:00:23
- geo_polygon :
- [[95.06959008486952, 29.814255053135895], [95.32812062059084, 29.809951334550703], [95.58659184122865, 29.80514261876954], [95.84499718862224, 29.7998293459177], [96.10333011481168, 29.79401200205343], [96.11032804508507, 30.019297601073085], [96.11740568350054, 30.244573983323825], [96.12456379063154, 30.469841094022847], [96.1318031397002, 30.695098878594504], [95.87110827645229, 30.70112924501256], [95.61033817656023, 30.7066371044805], [95.34949964126946, 30.711621947056347], [95.08859948278467, 30.716083310981194], [95.08376623410525, 30.49063893600811], [95.07898726183609, 30.26518607254204], [95.0742620484426, 30.039724763743482], [95.06959008486952, 29.814255053135895]]
- institution :
- NASA Jet Propulsion Laboratory (JPL), California Institute of Technology
- latitude :
- 30.26
- longitude :
- 95.6
- proj_polygon :
- [[700000, 3300000], [725000.0, 3300000.0], [750000.0, 3300000.0], [775000.0, 3300000.0], [800000, 3300000], [800000.0, 3325000.0], [800000.0, 3350000.0], [800000.0, 3375000.0], [800000, 3400000], [775000.0, 3400000.0], [750000.0, 3400000.0], [725000.0, 3400000.0], [700000, 3400000], [700000.0, 3375000.0], [700000.0, 3350000.0], [700000.0, 3325000.0], [700000, 3300000]]
- projection :
- 32646
- s3 :
- s3://its-live-data/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.zarr
- skipped_granules :
- s3://its-live-data/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.json
- time_standard_img1 :
- UTC
- time_standard_img2 :
- UTC
- title :
- ITS_LIVE datacube of image pair velocities
- url :
- https://its-live-data.s3.amazonaws.com/datacubes/v2/N30E090/ITS_LIVE_vel_EPSG32646_G0120_X750000_Y3350000.zarr
s2_subset.v.mean(dim='mid_date').plot();
ITS_LIVE is exciting because it combines velocity data from a number of satellites into one accessible and efficient dataset. From this brief look, you can see snapshot overviews of the different data within the dataset and begin to think about processing steps you might take to work with the data further.
Checking coverage along a dimension#
It would be nice to be able to scan/visualize and observe coverage of a variable along a dimension
First need to make a mask that will tell us all the possible ‘valid’ pixels. ie pixels over ice v. rock.
valid_pixels = sample_glacier_raster.v.count(dim=['x','y'])
valid_pix_max = sample_glacier_raster.v.notnull().any('mid_date').sum(['x','y'])
sample_glacier_raster['cov'] = valid_pixels/valid_pix_max
#how many time steps are duplicates?, there are 16872 unique vals in mid_dates
np.unique(sample_glacier_raster['mid_date'].data).shape
(3018,)
Start by grouping over mid_date. Would expect 16,872 (# unique time steps) with mostly groups of 1, groups of more than one on duplicate coords
test_gb = sample_glacier_raster.groupby(sample_glacier_raster.mid_date)
type(test_gb.groups)
dict
test_gb.groups is a dict, so let’s explore that object. the keys correspond to mid_date coords, so the values should be the entries at that coordinate.
Exploring data coverage over time series#
Let’s take a look at the data coverage over this glacier across the time series:
fig, ax = plt.subplots(figsize=(30,3))
sample_glacier_raster.cov.plot(ax=ax, linestyle='None',marker = 'x')
[<matplotlib.lines.Line2D at 0x7f7f5cc8dc50>]
But what if we wanted to explore the relative coverage of the different sensors that make up the its_live dataset as a whole?
We can use groupby to group the data based on a single condition such as satellite_img1 or mid_date.
sample_glacier_raster.cov.groupby(sample_glacier_raster.satellite_img1)
DataArrayGroupBy, grouped over 'satellite_img1'
5 groups with labels '1A', '2A', '2B', '7', '8'.
sample_glacier_raster.groupby('mid_date')
DatasetGroupBy, grouped over 'mid_date'
3018 groups with labels 2017-01-01T16:15:50.6605240....
However, if we want to examine the coverage of data from different sensor groups over time, we would essentially want to groupby two groups. To do this, we use flox
import flox.xarray
This is the xr.DataArray on which we will perform the grouping operation using flox
sample_glacier_raster.cov
<xarray.DataArray 'cov' (mid_date: 3974)>
array([0. , 0. , 0.0036784, ..., 0. , 0. ,
0. ])
Coordinates:
* mid_date (mid_date) datetime64[ns] 2018-04-14T04:18:49.171219968 ... 201...
mapping int64 0- mid_date: 3974
- 0.0 0.0 0.003678 0.0 0.0247 0.06569 0.2007 ... 0.0 0.0 0.0 0.0 0.0 0.0
array([0. , 0. , 0.0036784, ..., 0. , 0. , 0. ]) - mid_date(mid_date)datetime64[ns]2018-04-14T04:18:49.171219968 .....
- description :
- midpoint of image 1 and image 2 acquisition date and time with granule's centroid longitude and latitude as microseconds
- standard_name :
- image_pair_center_date_with_time_separation
array(['2018-04-14T04:18:49.171219968', '2017-02-10T16:15:50.660901120', '2019-03-15T04:15:44.180925952', ..., '2018-06-11T04:10:57.953189888', '2017-05-27T04:10:08.145324032', '2017-05-07T04:11:30.865388288'], dtype='datetime64[ns]') - mapping()int640
- crs_wkt :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- WGS 84
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- WGS 84 / UTM zone 46N
- grid_mapping_name :
- transverse_mercator
- latitude_of_projection_origin :
- 0.0
- longitude_of_central_meridian :
- 93.0
- false_easting :
- 500000.0
- false_northing :
- 0.0
- scale_factor_at_central_meridian :
- 0.9996
- spatial_ref :
- PROJCS["WGS 84 / UTM zone 46N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",93],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32646"]]
- GeoTransform :
- 700192.5 120.0 0.0 3394687.5 0.0 -120.0
array(0)
- mid_datePandasIndex
PandasIndex(DatetimeIndex(['2018-04-14 04:18:49.171219968', '2017-02-10 16:15:50.660901120', '2019-03-15 04:15:44.180925952', '2019-07-20 16:15:55.190603008', '2018-01-31 16:15:50.170811904', '2017-12-17 16:15:50.170508800', '2017-10-16 04:18:49.170811904', '2017-11-27 16:20:45.171105024', '2017-10-08 16:17:55.170906112', '2019-10-23 16:18:15.191001088', ... '2017-10-06 04:11:40.987761920', '2018-03-31 04:10:01.464065024', '2018-06-11 04:09:32.921265664', '2017-07-26 04:11:49.029760256', '2017-04-21 04:11:32.560144896', '2017-09-12 04:11:46.053865984', '2017-06-24 04:11:18.708142080', '2018-06-11 04:10:57.953189888', '2017-05-27 04:10:08.145324032', '2017-05-07 04:11:30.865388288'], dtype='datetime64[ns]', name='mid_date', length=3974, freq=None))
Using flox, we will define a coverage object that takes as inputs the data we want to reduce, the groups we want to use to group the data and the reduction we want to perform.
coverage = flox.xarray.xarray_reduce(
# array to reduce
sample_glacier_raster.cov,
# Grouping by two variables
sample_glacier_raster.satellite_img1.compute(),
sample_glacier_raster.mid_date,
# reduction to apply in each group
func="mean",
# for when no elements exist in a group
fill_value=0,
)
Now we can visualize the coverage over time for each sensor in the its_live dataset. Cool!
plt.pcolormesh(coverage.mid_date, coverage.satellite_img1, coverage, cmap='magma')
plt.colorbar();
Conclusion#
This notebook displayed basic data inspection steps that you can take when working with a new dataset. The following notebooks will demonstrate further processing, analytical and visualization steps you can take. We will be working with the same object in the following notebook, so we can use cell magic to store the object and read it in in the next notebook, rather than making it all over again. You can read more about the magic command here.
%store sample_glacier_raster
Stored 'sample_glacier_raster' (Dataset)